Alternative Data News. 11, September 2019

Finding sources and uses for alternative data can be difficult. At CloudQuant we regularly read and search the internet for new sources of data that can be used in our mission to find alpha signals and build quantitative trading strategies. We recognize that we are technology and data junkies so we wrote our own crawler that specifically seeks out web pages, posts, and news articles that give us a snapshot of what is going on in the world of Alt Data. The following is a collection of articles that we think you will find interesting from the past week.

Alternative Data Trends and Statistics

Alternative data is defined as non-traditional data investors use to gain insights into their investment process. Unlike traditional datasets data such as financial statements and sales figures, alternative data offers investors insights into a company well before the information becomes publicly available.

The case with WeWork’s IPO is great Example. Despite the hype around WeWork’s IPO, Director, Samantha Monk, predicted against popular consensus that WeWork is not the market-defying unicorn most hope it would be. With the help of alternative datasets, she identified several alarming issues such as founder cashout, creative accounting practices and ESG concerns. Most importantly, she was able to pinpoint Softbank’s reluctance to go ahead with Wework’s IPO ahead of Softbank’s announcement yesterday.

The explosion of alternative data has levelled the playing field between ordinary investors and hedge fund managers, allowing anyone with a laptop and internet access (and the willingness to learn) to deliver market-beating performance.
2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 8.6331, Raw Interest Score: 2.4087,
Positive Sentiment: 0.5439, Negative Sentiment 0.2331

CloudQuant Thoughts… WeWork (NYSE:WORK) has had an alarming fall from its IPO mid July just under $40 to this week’s low of under $24. Samantha’s article is here but do note that Samantha works for the Alternate data firm she is referencing – Meltwater. It is not clear if Meltwaters “Signals” generates signals or just highlights articles that may be of interest. The “What is Alternative Data” infographic at the main “Read the full story…” link is a nice introduction to Alternate Data.

Hedge funds of all sizes are using more alternative data, but concerns remain, says Lowenstein Sandler survey

Over 80 per cent of hedge funds are using alternative data in some capacity, according to a new survey fro law firm Lowenstein Sandler’s Investment Management Group.

The report – Alternative Data = Better Investment Strategies, But Not Without Concerns – was authored by Peter D Greene, partner and Vice Chair of Lowenstein’s Investment Management Group, with contributions from Benjamin Kozinn, a partner in that group.

“It is not surprising to me that an overwhelming majority of funds are using alternative data,” says Greene. “What is interesting is how funds of various sizes are using it and how they plan to expand their use in the future. In a changing industry, it is more important than ever to learn what alternative data can do, while also acknowledging the limitations and concerns that come with using such data.”

2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 7.2946, Raw Interest Score: 2.3484,
Positive Sentiment: 0.1638, Negative Sentiment 0.1365

CloudQuant Thoughts… 80% of hedgefunds use Alternative Data, and 81% plan to increase their budgets by 11-25 per cent. This is a growing market but as the article points out, the inability to identify “relevant” information is a limiting factor. CloudQuant is working on an approach to resolve this issue, by serving up data using a standardized system the ETL is almost eliminated, users can view large amounts of data, select data that interests them. They can receive CQ independant White Papers on the data, as well as the code used to generate the results which can be run on CloudQuant’s Mariner backtester, thus eliminating the common “reproducability” issue.

IBM Expands Cloud Pak for Data with New DataOps Enhancements

“IBM today announced enhancements to Cloud Pak for Data that leverage the DataOps methodology to help clients get their data ‘business-ready’ for AI. As corporate data continues to grow in both volume and complexity – often of mixed structures and types and from sources strewn across the enterprise – the time required to collect and organize these vast datasets into usable data for AI can stress resources and actually stall AI projects. Improving data preparation, management and automation are the pillars of the burgeoning and collaborative DataOps (data operations) principle, which outlines methods for automating and streamlining data flows across an enterprise. DataOps is also at the core of the “Organize” rung of IBM’s AI Ladder strategy, from which clients can transform datasets into data that’s tuned and prepared for AI.”
2019-09-11 07:10:51+00:00 Read the full story…
Weighted Interest Score: 5.7002, Raw Interest Score: 2.4079,
Positive Sentiment: 0.2457, Negative Sentiment 0.0491

CloudQuant Thoughts… Everyone in Big Data is experiencing the same issues at the moment. As they say in the article, getting mixed data with mixed structure “Business Ready” consumes time and resources stressing and sometimes stalling AI projects. CloudQuant has also been tackling these issues head on and will shortly make available many of the solutions it has created to “Eliminate the Bid Data Bottleneck”.

Google launches TensorFlow machine learning framework for graphical data

Google today introduced Neural Structured Learning (NSL), an open source framework that uses the Neural Graph Learning method for training neural networks with graphs and structured data.

NSL works with with the TensorFlow machine learning platform and is made to work for both experienced and inexperienced machine learning practitioners. NSL can make models for computer vision, perform NLP, and run predictions from graphical datasets like medical records or knowledge graphs.

“Leveraging structured signals during training allows developers to achieve higher model accuracy, particularly when the amount of labeled data is relatively small,” TensorFlow engineers said in a blog post today. “Training with structured signals also leads to more robust models. These techniques have been widely used in Google for improving model performance, such as learning image semantic embedding.”
2019-09-03 00:00:00 Read the full story…
Weighted Interest Score: 5.1086, Raw Interest Score: 2.8169,
Positive Sentiment: 0.1280, Negative Sentiment 0.1280

CloudQuant Thoughts… Simplifying the process of learning from graphical information is another tremendous step forward for ML/AI.

The explosion of ‘alternative’ data gives regular investors access to tools previously employed only by hedge funds

“Alternative data” is going mainstream as fund managers are projected to spend more than $1 billion this year to beat the market averages and stave off the rise of low-cost passive investing.

The explosive growth in the amount of alternative data sets — an array of information gleaned from the web, satellites and even consumers’ wallets — hasn’t proved to be a panacea. But what was once considered the domain of quantitatively oriented hedge funds and other well-heeled investors has become a must-have for traditional asset managers struggling to deliver market-beating returns.

Traditional investment managers face three options, said Octavio Marenzi, chief executive officer of Opimas, a capital-markets-focused management consulting firm. The first option is to embrace alternative data and effectively adopt a more quantitative approach. The second is to go into passive investing, tracking an index and abandoning research altogether. “And the third option is to go home and give up,” he told MarketWatch.
2019-09-05 00:00:00 Read the full story…
Weighted Interest Score: 4.7307, Raw Interest Score: 2.0120,
Positive Sentiment: 0.1210, Negative Sentiment 0.0908

CloudQuant Thoughts… “Adapt or die” is now “Go alternative, go passive or go home.”. It is obvious that we are in a new world in alternative data for investment. It does not take long for the Alpha to be extracted from a new Alternative Data set, so it is not enough to just get on-board, you have to get ahead and get the new data before anyone else!

Google open-sources datasets for AI assistants with human-level understanding

Google today open-sourced Coached Conversational Preference Elicitation (CCPE) and Taskmaster-1, datasets of dialog between two people. Both datasets are being shared by Google AI researchers to supply the training material necessary to model natural language systems that achieve human-level performance.

Google researchers call CCPE a new way to collect voice data. It includes 500 dialogues with people about their movie preferences — 10,000 in total, across 12,000 utterances.

Movie preferences were chosen as a topic because of the value of metadata such as the names of actors and directors.

“We do not restrict the workers to detailed scripts or to a small knowledge base and hence we observe that our dataset contains more realistic and diverse conversations in comparison to existing datasets,” a paper published covering CCPE reads.
2019-09-06 00:00:00 Read the full story…
Weighted Interest Score: 4.6865, Raw Interest Score: 1.5216,
Positive Sentiment: 0.1217, Negative Sentiment 0.0000

Bloomberg is investing in ways to make complex alternative data sets easier to use for hedge funds

One of the largest data providers in the world wants to make it easier for investors to digest complex, unique data sets.

Bloomberg LP is working to help investment firms, such as hedge funds, use alternative data despite lacking the resources or experience often required to digest it. The efforts come just over six months after Bloomberg announced a move into the booming market for data such as stats on drug approvals, retail foot traffic tracked through cellphones, and construction permits.

Bloomberg is now wo…
2019-09-04 00:00:00 Read the full story…
Weighted Interest Score: 3.9776, Raw Interest Score: 1.7391,
Positive Sentiment: 0.2569, Negative Sentiment 0.1383

6 Tips for Building a Training Data Strategy for Machine Learning

Without a well-defined approach for collecting and structuring training data, launching an AI initiative becomes an uphill battle. These six recommendations will help you craft a successful strategy.

By Wilson Pang, CTO, Appen.

Artificial intelligence (AI) and machine learning (ML) are frequently used terms these days. AI refers to the concept of machines mimicking human cognition. ML is an approach used to create AI. If AI is when a computer c…
2019-09-06 00:00:00 Read the full story…
Weighted Interest Score: 3.8282, Raw Interest Score: 1.9417,
Positive Sentiment: 0.2222, Negative Sentiment 0.1755

Explorium raises $19 million to unify AI model training and deployment

Explorium, a Tel Aviv-based startup developing what it describes as an automated data and feature discovery platform, today announced that it’s raised $19 million total across several funding rounds. Emerge and F2 Capital contributed $3.6 million in a seed raise, and Zeev Ventures led a $15.5 million in series A.

The influx of capital comes after a banner year for Explorium, during which says it nabbed Fortune 100 customers in industries ranging…
2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 3.8059, Raw Interest Score: 2.0019,
Positive Sentiment: 0.0636, Negative Sentiment 0.0318

Sentieo’s AI-focused research platform supercharges equity analysts’ stock picking capabilities

In a world awash with data, hedge fund equity analysts looking for that one data point that could generate alpha face a significant challenge, akin to finding a needle in a haystack. But as data volumes have grown, so too has the pace of technology innovation.

There is now an impressive array of technology solutions to support the buy-side. One of these firms is Sentieo, a financial data platform utilising artificial intelligence and cutting edg…
2019-09-06 00:00:00 Read the full story…
Weighted Interest Score: 3.7696, Raw Interest Score: 1.7226,
Positive Sentiment: 0.1656, Negative Sentiment 0.0552

Explorium reveals $19.1M in total funding for machine learning data discovery platform – TechCrunch

Explorium, a data discovery platform for machine learning models, received a couple of unannounced funding rounds over the last year — a $3.6 million seed round last September and a $15.5 million Series A round in March. Today, it made both of these rounds public.

The seed round was led by Emerge with participation of F2 Capital. The Series A was led by Zeev Ventures with participation from the seed investors. The total raised is $19.1 million.

2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 3.7006, Raw Interest Score: 1.8779,
Positive Sentiment: 0.2561, Negative Sentiment 0.2988

Data Strategy and Serverless Computing: How Do They Work Together?

Businesses need a strong Data Strategy to manage vast amounts of data, drive innovation, develop a data culture, and to maintain a competitive advantage. Though cloud environments offer fast, high-volume data collection and scalable storage space; machine learning-powered data preparation; AI-enabled analytics; data backup and recovery facilities — leaving the developers free to pursue coding.

Although cloud security is still a common concern, t…
2019-09-10 07:35:33+00:00 Read the full story…
Weighted Interest Score: 3.6230, Raw Interest Score: 2.0532,
Positive Sentiment: 0.2369, Negative Sentiment 0.1579

ArangoDB: Three Databases In One

a German database expanding its business in the United States, has released new capabilities in version 3.5 of its eponymous database management software to make it easier to query and search growing data sets across multiple data models. With ArangoDB, data can be stored as key-value pairs, graphs or documents and accessed with one declarative query language. And you can do both at the same time — a document query and a graph query. The combination offers flexibility and performance advantages, explained Claudius Weinberger, CEO. (Source: The New Stack)…
2019-09-06 02:06:25+00:00 Read the full story…
Weighted Interest Score: 3.5088, Raw Interest Score: 2.6316,
Positive Sentiment: 0.3509, Negative Sentiment 0.0000

R.I.P. Python 2: October 16, 2000 — January 1, 2020

R.I.P. Python 2: October 16, 2000 — January 1, 2020 Synced Follow Sep 9 · 3 min read

The development and maintenance team behind Python 2 has started the countdown to the end of the popular programming language. In an official statement released today on, the volunteer team that manages the programming language announced they will sunset Python 2 on January 1, 2020.

“That means that we will not improve it anymore after that day, even…
2019-09-09 17:52:55.349000+00:00 Read the full story…
Weighted Interest Score: 3.4131, Raw Interest Score: 2.1185,
Positive Sentiment: 0.3138, Negative Sentiment 0.1177

Is It Time To Consider Buying Rain Industries Limited (NSE:RAIN)?

Rain Industries Limited (NSE:RAIN), which is in the chemicals business, and is based in India, saw a double-digit share price rise of over 10% in the past couple of months on the NSEI. As a small cap stock, hardly covered by any analysts, there is generally more of an opportunity for mispricing as there is less activity to push the stock closer to fair value. Is there still an opportunity here to buy? Let’s take a look at Rain Industries’s outloo…
2019-09-09 18:51:27+10:00 Read the full story…
Weighted Interest Score: 3.1550, Raw Interest Score: 1.7092,
Positive Sentiment: 0.2973, Negative Sentiment 0.0991

The thin line between data science and data engineering

Editor’s note: This is the fourth episode of the Towards Data Science podcast “Climbing the Data Science Ladder” series, hosted by Jeremie Harris, Edouard Harris and Russell Pollari. Together, they run a data science mentorship startup called SharpestMinds. You can listen to the podcast below:

If you’ve been following developments in data science over the last few years, you’ll know that the field has evolved a lot since its Wild West phase in t…
2019-09-10 18:58:02.118000+00:00 Read the full story…
Weighted Interest Score: 3.1378, Raw Interest Score: 1.7053,
Positive Sentiment: 0.0682, Negative Sentiment 0.1364

Dutch startup Suburbia picked for Tokyo fintech accelerator programme

Source: Suburbia

Suburbia is the first Dutch startup ever to be selected for Fintech Business Camp Tokyo, an accelerator program for young fintechs. The two-month program, which will kick off in October, is run by the office of the mayor of Tokyo with Accenture Japan.

“We feel really proud and honored to be the first and only Dutch startup picked for this program,” said Hamza Khan, CEO and founder of Suburbia, an Amsterdam-based tech company pr…
2019-09-11 14:32:00 Read the full story…
Weighted Interest Score: 2.9796, Raw Interest Score: 1.2507,
Positive Sentiment: 0.3127, Negative Sentiment 0.0000

Hong Kong exchange makes surprise US$36.6B bid for LSE

Hong Kong Exchanges & Clearing Ltd. made an unexpected US$36.6 billion bid for London Stock Exchange Group Plc, a bold move that would upend the U.K. bourse’s combination with Refinitiv.

LSE’s board “remains committed to” the acquisition of data provider Refinitiv, highlighting the hurdles facing an offer that it called unsolicited, preliminary and highly conditional. The board said it would consider the proposal and make a further announcement …
2019-09-11 05:10:10-04:00 Read the full story…
Weighted Interest Score: 2.9104, Raw Interest Score: 1.7735,
Positive Sentiment: 0.0455, Negative Sentiment 0.1592

Google’s latest free tools tap into big data without destroying your privacy

Getty Images

Data about human beings can tell you countless helpful things. How crowded is a hospital waiting room on a typical Saturday? What’s the traffic like for your morning commute? But collecting all this data comes with the risk of exposing private information about individuals. When you want to know how busy a hospital is, you don’t need – or want – to know who was in the emergency room last Saturday.

That’s exactly the dilemma you fac…
2019-09-05 03:00:05-07:00 Read the full story…
Weighted Interest Score: 2.8326, Raw Interest Score: 1.4676,
Positive Sentiment: 0.0759, Negative Sentiment 0.2024

Why You Need To Re-Tool Your Skills To Future-Proof Your Job

The world now stands on the cusp of a technological revolution in artificial intelligence and robotics that may prove as transformative for economic growth and human potential as were electrification, mass production, and electronic telecommunications in their eras.

New and emerging technologies will raise aggregate economic output and boost the wealth of nations. Will these developments enable people to attain higher living standards, better wo…
2019-09-11 06:19:23+00:00 Read the full story…
Weighted Interest Score: 2.7967, Raw Interest Score: 1.3661,
Positive Sentiment: 0.3355, Negative Sentiment 0.2996

10 Indian Startups That Are Leading The AI Race: 2019

The Indian AI startups space is booming and now encompasses various avenues such as computer vision, self-driving, retail, audio production and innovating e-commerce platforms, among others. This year we have come with a list of yet another 10 awesome startups that are revolutionising the field of artificial intelligence with their impressive technologies. These startups are about two to three years old and are already beginning to show some rema…
2019-09-04 07:33:17+00:00 Read the full story…
Weighted Interest Score: 2.7880, Raw Interest Score: 1.4398,
Positive Sentiment: 0.2475, Negative Sentiment 0.0900

Hong Kong Stock Exchange Bids For London Rival

said Wednesday.

The blockbuster proposal including debt, worth $40 billion or 36 billion euros, is dependent on the London Stock Exchange Group (LSEG) scrapping a proposed $27-billion takeover of US financial data provider Refinitiv.

In reaction, LSEG said it would “consider the proposal” but stressed that it “remains committed” to buying Refinitiv.

The surprise news sent LSE shares surging 6.3 percent to about £72, but far below the offer price of more than £83 per share.

London’s benchmark FTSE 100 index was up 0.9 percent overall in late morning deals.

Photo: AFP / Tolga AKMEN

“Hong Kong Exchange…
2019-09-11 05:52:35-04:00 Read the full story…
Weighted Interest Score: 2.7583, Raw Interest Score: 2.0103,
Positive Sentiment: 0.1870, Negative Sentiment 0.1403

Asian markets gain ahead of ECB meeting

Asian markets mostly gained in early trading Wednesday, ahead of expected further monetary easing by the European Central Bank.

The ECB is expected to take rates even deeper into negative territory at its Thursday meeting. Policy makers have indicated the ECB could introduce a tiered system of deposits, which would see only a portion of deposits subject to negative rates, which could ease a further hit to the banking sector’s profitability.

2019-09-10 00:00:00 Read the full story…
Weighted Interest Score: 2.7464, Raw Interest Score: 1.5437,
Positive Sentiment: 0.3431, Negative Sentiment 0.3185

Data Modeling in an Agile World

Data Modeling creates a model for storing and processing data that works in a predictable, consistent manner. It includes the visual presentation of data structures, while enforcing business rules and government policies. A data model focuses on the needed data and its organization, rather than the operations performed on the data. Data Modeling is done by professional data modelers, who work closely with business managers and staff to create fun…
2019-09-04 07:35:13+00:00 Read the full story…
Weighted Interest Score: 2.7430, Raw Interest Score: 1.8962,
Positive Sentiment: 0.2266, Negative Sentiment 0.2027

A 2019 Guide to Speech Synthesis with Deep Learning

In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

By Derrick Mwiti, Data Analyst.

Artificial production of human speech is known as speech synthesis. This machine learning-based technique is applicable in text-to-speech, music generation, speech generation, speech-enabled devices, navigation systems, and accessibility for visually-impaired people.

In th…
2019-09-20 00:00:00 Read the full story…
Weighted Interest Score: 2.7118, Raw Interest Score: 1.7903,
Positive Sentiment: 0.1377, Negative Sentiment 0.1018

AI researchers translate language into physical movement

Carnegie Mellon University AI researchers have created an AI agent that is able to translate words into physical movement. Called Joint Language-to-Pose, or JL2P, the approach combines natural language with 3D pose models. The pose forecasting joint embedding is trained with end-to-end curriculum learning, an approach that stresses shorter task completion sequences before moving on to harder objectives.

JL2P animations are limited to stick figur…
2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 2.6805, Raw Interest Score: 1.3835,
Positive Sentiment: 0.1729, Negative Sentiment 0.2162

UBS commissions installation to visualise air pollution

UBS has come up with a novel way to show off its big data capabilities, enlisting designer Elaine Yan Ling Ng to create an interactive installation that explores global air quality through a feed of data from monitoring stations around the world.

How polluted is the air today? ‘Nexus’, Elaine Yan Ling Ng’s sculpture on view in the @UBSglobalart lounge, has the answer. Using light patterns and @UBS Evidence Lab data from 8,000+ air quality monito…
2019-09-11 00:01:00 Read the full story…
Weighted Interest Score: 2.5502, Raw Interest Score: 1.2722,
Positive Sentiment: 0.0771, Negative Sentiment 0.0386

10 Exciting Papers To Look Out For At The NeurIPS 2019 Conference

The 33rd annual conference on Neural Information Processing Systems (NeurIPS) is going to be held at Vancouver Convention Center, Vancouver, Canada from December 8th to 14th, 2019.

The primary focus of the Foundation is the presentation of a continuing series of professional meetings known as the Neural Information Processing Systems Conference, held over the years at various locations in the United States, Canada and Spain.

NeurIPS received a …
2019-09-09 13:30:03+00:00 Read the full story…
Weighted Interest Score: 2.5425, Raw Interest Score: 1.8751,
Positive Sentiment: 0.2225, Negative Sentiment 0.1430

Implementing Random Forest in R

Implementing Random Forest in R

A Practical Application of Random Forest in Classifying Breast Cancer Patients

Photo by Rural Explorer on Unsplash

What is Random Forest (RF)?

In order to understand RF, we need to first understand about decision trees. Rajesh S. Brid wrote a detailed article about decision trees. We will not go too much in details about the definition of decision trees since that is not the purpose of this article. I just want…
2019-09-11 13:42:39.666000+00:00 Read the full story…
Weighted Interest Score: 2.5306, Raw Interest Score: 1.3496,
Positive Sentiment: 0.1546, Negative Sentiment 0.1687

Tutela acquired by Comlinkdata

Telecom market data firm Comlinkdata has acquired crowdsourced mobile network and performance data company Tutela for an undisclosed sum.

Tutela gathers device-based data on mobile usage and performance; its software runs in the background in thousands of Android and iOS smartphone apps to deliver anonymized data on user experience and behavior. The company says it collects more than 30 billion device, application and network data points each da…
2019-09-09 00:00:00 Read the full story…
Weighted Interest Score: 2.5210, Raw Interest Score: 1.3575,
Positive Sentiment: 0.3232, Negative Sentiment 0.1616

How Data Services Sourcing Options are Changing in Financial Services

By Mark Hepsworth, CEO, Asset Control

Many financial institutions are facing a perfect storm of pressure on revenues and increasing costs driven by regulatory mandates and the need for overdue investment in infrastructure. At the same time, they are funding projects to improve their competitive differentiation and support revenue growth. Against this backdrop many firms are adopting managed services to reduce costs, facilitate faster change and …
2019-09-02 09:38:30+00:00 Read the full story…
Weighted Interest Score: 2.5200, Raw Interest Score: 1.2746,
Positive Sentiment: 0.2303, Negative Sentiment 0.2918

Case Study: Nearmap Advances AI-driven Location Intelligence

missing valuable location data, then why not use artificial intelligence (AI) and machine learning (ML) to fill in the gaps? Take the image of Perth, Australia, below:

This graphic below shows vast data sets containing buildings, green spaces, roads to travel, and parking lots. Drill down even further and see rooftops, solar panels, fire hydrants, gas lines, and many other objects. And all this data constantly changes over time. City residents move, purchase new developments for their homes, drive roads with new potholes, and build new construction.

How is a person to keep up with it all? In a rece…
2019-09-05 07:35:17+00:00 Read the full story…
Weighted Interest Score: 2.5030, Raw Interest Score: 1.2154,
Positive Sentiment: 0.2366, Negative Sentiment 0.1398

Broadridge’s Latest Acquisition Is Financial Database Services

(Image: Shutterstock)

Broadridge Financial Solutions has strengthened its advisor compensation capabilities by acquiring San Diego-based Financial Database Services (FDS), Broadridge said Tuesday without disclosing the purchase price.

FDS, founded in 1989, developed Caesar, a back-office management solution for BDs, according to its LinkedIn profile. The company employs 18 people and Broadridge was planning to offer each of them jobs, according to Broadridge spokesman Gregg Rosenberg.

In addition to compensation management, FDS also provides c…
2019-09-03 00:00:00 Read the full story…
Weighted Interest Score: 2.4741, Raw Interest Score: 1.7255,
Positive Sentiment: 0.2006, Negative Sentiment 0.0803

Neural Network for Satellite Data Classification Using Tensorflow in Python

arning has taken over the majority of fields in solving complex problems, and the geospatial field is no exception. The title of the article interests you and hence, I hope that you are familiar with satellite datasets; for now, Landsat 5 TM. Little knowledge of how Machine Learning (ML) algorithms work, will help you grasp this hands-on tutorial quickly. For those who are unfamiliar with ML concept, in a nutshell, it is establishing the relationship between a few characteristics (features or Xs) of an entity with its other property (value or label or Y) — we provide plenty of examples (labelled data) to th…
2019-09-11 05:20:35.807000+00:00 Read the full story…
Weighted Interest Score: 2.4101, Raw Interest Score: 1.2997,
Positive Sentiment: 0.0753, Negative Sentiment 0.2825

Choosing Data Models for Big Data

At a high level, a data model defines the structure and meaning of data in a system. This shapes how you represent concepts of interest or entities and their relationships to each other. It also influences how you end up thinking about these entities. For example, one USER can own many Email ACCOUNTs, and each account can, in turn, own many EMAILs

There often isn’t one true answer for which data model should be used to represent a particular con…
2019-09-05 00:00:00 Read the full story…
Weighted Interest Score: 2.3881, Raw Interest Score: 1.3406,
Positive Sentiment: 0.1372, Negative Sentiment 0.1434

Epcor and Segmint to show banks how to monetize transaction data

Source: Epcor

EPCOR – Your Electronic Payments Core of Knowledge announced today that it has partnered with Segmint, a leading provider of data-driven solutions, to help financial institution members identify growth opportunities and build concentrated strategies by leveraging their existing payments data.

Member financial institutions of all sizes now have access to actionable insights and trends about their account holders and competitors via…
2019-09-11 14:40:00 Read the full story…
Weighted Interest Score: 2.3404, Raw Interest Score: 1.3830,
Positive Sentiment: 0.6383, Negative Sentiment 0.1064

European stock markets extend gains, as mega-merger eyed

European stocks jumped further Wednesday on the eve of a key ECB policy meeting, while investors gave a lukewarm response to a takeover bid for the London Stock Exchange by its Hong Kong rival.

News that US President Donald Trump had fired his hawkish national security adviser John Bolton also lifted sentiment, with analysts saying it could see the White House take a less strident approach and ease geopolitical tensions.

“Equities in Europe are…
2019-09-11 07:30:48-04:00 Read the full story…
Weighted Interest Score: 2.3140, Raw Interest Score: 1.7085,
Positive Sentiment: 0.1081, Negative Sentiment 0.3244

Hong Kong Stock Exchange unveils shock £32bn bid for London rival

sia and Europe.

The blockbuster proposal including debt, worth $40 billion or 36 billion euros, is dependent on the London Stock Exchange Group (LSEG) scrapping a proposed $27-billion takeover of US financial data provider Refinitiv.

In reaction, LSEG said it would “consider the proposal” but stressed that it “remains committed” to buying Refinitiv.

The surprise news initially sent LSEG shares surging 10 percent.

The stock later stood up 4.5 percent at about £71, far below the offer price of more than £83 per share as analysts doubted the likelihood of a deal being struck given LSEG’s commitment to Re…
2019-09-11 06:35:43-04:00 Read the full story…
Weighted Interest Score: 2.1855, Raw Interest Score: 1.5923,
Positive Sentiment: 0.1561, Negative Sentiment 0.2498

Detecting Abnormal Weather Patterns With Data Science Tools

Detecting Abnormal Weather Patterns With Data Science Tools Countries around the world are grappling with more extreme weather events. But how do you pinpoint these outliers exactly? Chua Chin Hon Follow Sep 11 · 10 min read

A large waterspout spotted off the east coast of Singapore on August 6 2016. Photo: Chua Chin Hon

Around the world, extreme weather events are becoming more intense and frequent. There’s no missing some of these major weath…
2019-09-11 13:44:23.721000+00:00 Read the full story…
Weighted Interest Score: 2.1117, Raw Interest Score: 0.8001,
Positive Sentiment: 0.1873, Negative Sentiment 0.2383

Procella: unifying serving and analytical data at YouTube

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., VLDB’19

Academic papers aren’t usually set to music, but if they were the chorus of Queen’s “I want it all (and I want it now…)” seems appropriate here. Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here could well be the future of data processing at Google. Well, I say the future, but “Procella has now been in produc…
2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 2.0867, Raw Interest Score: 1.2936,
Positive Sentiment: 0.2172, Negative Sentiment 0.1039

How Microsoft got in on the creation of the world’s first whisky formulated with AI

BOT or NOT? This special series explores the evolving relationship between humans and machines, examining the ways that robots, artificial intelligence and automation are impacting our work and lives.

Computer scientists have tried using artificial intelligence to write poetry and compose music, with mixed results. But have they tried using it to make whisky?

We now know that they have, although drinkers in the U.S. will have to wait to judge h…
2019-09-06 01:52:20-07:00 Read the full story…
Weighted Interest Score: 2.0622, Raw Interest Score: 1.1559,
Positive Sentiment: 0.0701, Negative Sentiment 0.0350

The 5 Graph Algorithms That Data Scientists Should Know

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

By Rahul Agarwal, Data Scientist at Walmart Labs

We as data scientists have gotten quite comfortable with Pandas or SQL or any other relational database.

We are used to seeing our users in rows with their attributes as columns. But does the real world really behave like that?

In a connected world, us…
2019-09-05 00:00:00 Read the full story…
Weighted Interest Score: 2.0288, Raw Interest Score: 0.6989,
Positive Sentiment: 0.1075, Negative Sentiment 0.0874

Great Expectations: the economic power of news about the future

Silvia Miranda-Agrippino, Sinem Hacioglu Hoke and Kristina Bluwstein

Can shifts in beliefs about the future alter the macroeconomic present? This post summarizes our recent working paper where we have combined data on patent applications and survey forecasts to isolate news of potential future technological progress, and studied how macroeconomic aggregates respond to them. We have found news-induced changes in beliefs to be powerful enough to e…
2019-09-11 08:00:00+00:00 Read the full story…
Weighted Interest Score: 1.9641, Raw Interest Score: 0.8700,
Positive Sentiment: 0.2332, Negative Sentiment 0.2242

Warning – Unintended CSDR Consequences Ahead

CREST Matching is Changing

CREST has been operating successfully for over 20 years and has been part of the Euroclear Group since 2002. For the majority of that time its rules and processes have remained stable, known, and well understood. Larger market players have integrated their settlement processing into the CSD via the GUI, FT, or ISO interfaces, and achieve high STP and settlement success rates. CREST settles approximately £340bn in value…
2019-09-10 12:04:43 Read the full story…
Weighted Interest Score: 1.9556, Raw Interest Score: 1.0718,
Positive Sentiment: 0.1316, Negative Sentiment 0.3949

How an AI Startup Designed a Drug Candidate in Just 46 Days

Discovering a new drug can take decades, billions of dollars, and untold man hours from some of the smartest people on the planet. Now a startup says it’s taken a significant step towards speeding the process up using AI.

The typical drug discovery process involves carrying out physical tests on enormous libraries of molecules, and even with the help of robotics it’s an arduous process. The idea of sidestepping this by using computers to virtual…
2019-09-09 00:00:00 Read the full story…
Weighted Interest Score: 1.8888, Raw Interest Score: 0.8635,
Positive Sentiment: 0.2428, Negative Sentiment 0.1079

Trump Calls Federal Reserve Officials ‘Boneheads,’ Demands Zero Interest Rates

President Donald Trump renewed his attack on the Federal Reserve Wednesday, calling the central bank’s policymakers ‘boneheads’ as he called for U.S. interest rates to be cut to zero percent.

The latest attack on Fed Chairman Jerome Powell, whom Trump appointed last year, comes as policymakers at the European Central Bank meet today in Frankfurt for the start of of a two-day discussion that is likely to see President Mario Draghi deliver deeper …
2019-09-11 07:27:17-04:00 Read the full story…
Weighted Interest Score: 1.8809, Raw Interest Score: 1.3428,
Positive Sentiment: 0.1975, Negative Sentiment 0.3160

Object Detection in the City

Object Detection in the City

Taking my Android model on a tour through the city of Siem Reap

Ta Prohm. Siem Reap, Cambodia. Photo by me.

What’s better than a machine learning model? A deployed one. A model that’s actively producing something. The opposite of it is what I like to call “PowerPoint AI,” models that only live inside a presentation made of 57 slides. This kind of black boxes, as impressive and shiny as they sound, haven’t had the c…
2019-09-11 13:45:08.318000+00:00 Read the full story…
Weighted Interest Score: 1.6903, Raw Interest Score: 0.7196,
Positive Sentiment: 0.1619, Negative Sentiment 0.0720

FS organisations require a more sophisticated level of threat protection, here’s why

The financial services industry continues to be a prime target for cyber criminals. The opportunities available to steal payment card data, online banking accounts, compromise ATM machines using ransomware, cryptomining, and other malware, is simply too tempting. And the rate and sophistication of attacks is only getting more difficult to manage and protect against. The transitionary period many financial services organisations find themselves in…
2019-09-10 15:13:25 Read the full story…
Weighted Interest Score: 1.6878, Raw Interest Score: 1.0139,
Positive Sentiment: 0.1690, Negative Sentiment 0.5492

ESG Investing – The Search for Ground Truth

Pundits were recently fawning over the proclamation by 180 companies – including some of our favorite dividend growth investing names like Johnson & Johnson (JNJ), 3M (MMM), and The Coca-Cola Company (KO) – that maximizing shareholder value is no longer the raison d’etre for these companies. This slap in the face of fiduciary responsibility should be firmly denounced by all investors because the premise is preposterous. The “evil capitalist corpo…
2019-09-03 12:09:26+00:00 Read the full story…
Weighted Interest Score: 1.6733, Raw Interest Score: 0.8995,
Positive Sentiment: 0.3544, Negative Sentiment 0.1090

Apple unveils Research app with heart and women’s health studies

Apple today unveiled the Apple Research app for iPhone and Apple Watch users interested in sharing their health data, along with a series of studies with major health research organizations.

Apple also unveiled iPhone 11, Apple Watch Series 5, 7th generation iPad, game subscription service Arcade, and Apple TV+. The news was announced today in a presentation at Steve Jobs Theater at Apple headquarters in Cupertino, California.

Studies introduced today include:

Apple Hearing Study to analyze the impact of ext…
2019-09-10 00:00:00 Read the full story…
Weighted Interest Score: 1.6399, Raw Interest Score: 1.2764,
Positive Sentiment: 0.0729, Negative Sentiment 0.1459

Euro dips to one-week low before ECB meeting

NEW YORK (Reuters) – The euro fell to a one-week low against the greenback on Wednesday, a day before the European Central Bank is expected to add further stimulus in a bid to boost the region’s economy.

FILE PHOTO: A Japan Yen note is seen in this illustration photo taken June 1, 2017. REUTERS/Thomas White/Illustration/File Photo

ECB policymakers are leaning toward a package that includes a rate cut, a beefed-up pledge to keep rates low for lo…
2019-09-11 13:51:34+00:00 Read the full story…
Weighted Interest Score: 1.6062, Raw Interest Score: 0.9637,
Positive Sentiment: 0.2295, Negative Sentiment 0.5966

Find Out How Much You’ve Spent on Amazon — Analyze Your Data

How Much Have You Spent on Amazon? Analyzing Amazon Data

How much money have I spent on Amazon? — That’s a question that will interest, and possibly terrify, longtime customers of the ecommerce giant. But if you want the answer, it is available. You can find out how much you’ve spent on Amazon, and quite a bit more.

Let’s walk through how.

We’re going to analyze our Amazon data using a little Python programming. But if you’ve never coded anyth…
2019-09-10 15:46:52+00:00 Read the full story…
Weighted Interest Score: 1.5734, Raw Interest Score: 0.9597,
Positive Sentiment: 0.1162, Negative Sentiment 0.0985

Multiprocessing vs. Threading in Python: What Every Data Scientist Needs to Know

Sooner or later, every data science project faces an inevitable challenge: speed. Working with larger data sets leads to slower processing thereof, so you’ll eventually have to think about optimizing your algorithm’s run time. As most of you already know, parallelization is a necessary step of this optimization. Python offers two built-in libraries for parallelization: multiprocessing and threading. In this article, we’ll explore how data scientists can go about choosing between the two and which factors …
2019-09-07 13:44:45+00:00 Read the full story…
Weighted Interest Score: 1.5660, Raw Interest Score: 0.7977,
Positive Sentiment: 0.1336, Negative Sentiment 0.2046

Secure Your Personal Information – Tips On Best Practices With Abine

ValueWalk’s interview with Will Simonds, the Head of Customer Success and Marketing at Abine, Inc. In this interview, Will discusses the major date breaches, the difference between a hack and a data breach, if Apple’s computers are immune to viruses, secruity measures the big tech firms are taking, if phones and smartwatches can be breached and if there is a way to secure them, their company’s product offerings that lets you remove your personal …
2019-09-10 15:26:42+00:00 Read the full story…
Weighted Interest Score: 1.5122, Raw Interest Score: 0.9830,
Positive Sentiment: 0.1650, Negative Sentiment 0.3574

Leadership Performance With 2nd Gen Intel Xeon Scalable Processors

April 2019 saw the launch of the 2nd-generation Intel® Xeon® Scalable processor (formerly codenamed Cascade Lake), a server-class processor. This new processor family has already set 95 performance world records, earning performance leadership. New features include Intel® Deep Learning Boost (Intel® DL Boost) for AI deep learning inference acceleration and support for Intel® Optane™ DC (data center) persistent memory. These processors will contin…
2019-09-04 09:33:44+00:00 Read the full story…
Weighted Interest Score: 1.4832, Raw Interest Score: 0.8560,
Positive Sentiment: 0.2882, Negative Sentiment 0.3814

Are first babies more likely to be late?

Are first babies more likely to be late?

Yes, and also more likely to be early. But just a little.

If you are pregnant with your first child, you might have heard that first babies are more likely to be late. Also, you might have heard that they are more likely to be early. As it turns out, both are true.

If “early” means preterm — before 37 weeks of pregnancy — first babies are more likely to be early. Based on live births recorded in the Nat…
2019-09-09 15:14:49.711000+00:00 Read the full story…
Weighted Interest Score: 1.4255, Raw Interest Score: 0.8495,
Positive Sentiment: 0.0288, Negative Sentiment 0.2304

A Primer to Recommendation Engines

Let’s say your friend asks you for a movie recommendation. How do you go about doing this? If you’re not too into movies and if it’s not a friend you know too well, perhaps you Google best movie on netflix and give your friend the answers to whatever listicle you find. Maybe your friend tells you their favorite genre is horror — you then recommend the best horror movie you know. Or, maybe your friend gives you examples of movies they like. You th…
2019-09-10 16:27:24.175000+00:00 Read the full story…
Weighted Interest Score: 1.3985, Raw Interest Score: 0.7152,
Positive Sentiment: 0.3155, Negative Sentiment 0.0631

Conditional Love: The Rise of Renormalization Techniques for Conditioning Neural Networks

Batch Normalization, and the zoo of related normalization strategies that have grown up around it, have played an interesting array of roles in recent deep learning research: as a wunderkind optimization trick, a focal point for discussions about theoretical rigor and, importantly, but somewhat more in the sidelines, as a flexible and broadly successful avenue for injecting conditioning information into models.

Conditional renormalization starte…
2019-09-10 03:55:48.562000+00:00 Read the full story…
Weighted Interest Score: 1.3593, Raw Interest Score: 0.9631,
Positive Sentiment: 0.1332, Negative Sentiment 0.1672

Five use cases for IoT in public safety and emergency response

How could IoT be used to support public safety?

The European Telecommunications Standards Institute recently examined the potential use of IoT devices in emergency situations, as well as the state of standards development for such use.

ETSI identified a number of use cases in which IoT devices could play a role in emergency situations. Five of those applications for IoT in public safety were:

Emergency calling. ETSI outlined two IoT-driven eme…
2019-09-10 00:00:00 Read the full story…
Weighted Interest Score: 1.3434, Raw Interest Score: 1.0596,
Positive Sentiment: 0.0757, Negative Sentiment 0.2081

Three Seattle startups make LinkedIn’s 2019 list of 50 hottest companies to work for now

LinkedIn’s 2019 list of the 50 Top Startups in the U.S. once again includes three companies from Seattle, with two unicorns and one fast-growing customer data platform making the cut.

The third annual look at the hottest companies to work for now features Amperity, Convoy and Outreach among a list of startups that are “growing massively, scrambling industries, shifting talent flows around the world and, often, altering how we work and live,” acc…
2019-09-04 22:32:10-07:00 Read the full story…
Weighted Interest Score: 1.3342, Raw Interest Score: 0.9762,
Positive Sentiment: 0.0000, Negative Sentiment 0.0651

Big Data’s Role In Childbirth And Maternal Death In The US

Maternal mortality rates in the United States jumped over 25% between 2000 and 2013. The CDC uses data to better understand why the United States has the highest maternal death rates in the developed world. Big data allows researchers to dig deeper into the issue to better understand what’s occurring that’s leading to increased deaths for mothers.

Understaffed hospitals and medical errors are causing most of the deaths.

Big Data’s Role in the E…
2019-09-04 19:47:14+00:00 Read the full story…
Weighted Interest Score: 1.3296, Raw Interest Score: 0.8322,
Positive Sentiment: 0.4993, Negative Sentiment 0.1387

No poop required: Researchers devise blood test for gut microbiome diversity using data from defunct startup Arivale

If you want to know what’s going on in your gut microbiome, the community of bacteria in our intestines that are tied to overall health, there are plenty of companies willing to help. You just have to pay them — and send in a poop sample.

But it turns out that bottling feces isn’t the only way to gain insights into the gut. Researchers at the Institute for Systems Biology (ISB) in Seattle have devised a new way to look into the state of your mic…
2019-09-02 15:00:53-07:00 Read the full story…
Weighted Interest Score: 1.2540, Raw Interest Score: 0.7204,
Positive Sentiment: 0.1334, Negative Sentiment 0.2134

Survey: Challenges Faced In Data Science Sector — 2019

Analytics and Data Science industry has seen a sharp increase in terms of demand for insights and has opened jobs for highly-skilled professionals. Be it Fortune 500 name or startups — everyone is using analytics to garner insights from data. However, the industry is still riddled with a lot of challenges in terms of talent, reaching the right consumers and gathering data, among others.

This month Analytics India Magazine decided to find out wha…
2019-09-09 10:33:56+00:00 Read the full story…
Weighted Interest Score: 1.0567, Raw Interest Score: 0.6364,
Positive Sentiment: 0.1681, Negative Sentiment 0.4803

Face recognition, bad people and bad data — Benedict Evans

This works fantastically well for a whole class of problem, including face recognition, but it introduces two areas for error.

First, what exactly is in the training data – in your examples of X and Not-X? Are you sure? What ELSE is in those example sets?

My favourite example of what can go wrong here comes from a project for recognising cancer in photos of skin. The obvious problem is that you might not have an appropriate distribution of samp…
2019-09-06 00:00:00 Read the full story…
Weighted Interest Score: 0.9609, Raw Interest Score: 0.6914,
Positive Sentiment: 0.0884, Negative Sentiment 0.3379

iPhone 11: Release, Specs, Features, Cost and Rumors

Apple (AAPL – Get Report) hosted their annual event earlier today and announced, among other things, the newest iPhone.

A lot of rumors and speculation surrounding the iPhone 11 had been floating around the internet for weeks, and thanks to Apple’s giant event we now know what was true, what wasn’t and some features that had not been reported on prior to this. In classic Apple fashion, they tried to keep things as discrete as possible leading up…
2019-09-10 16:32:49-04:00 Read the full story…
Weighted Interest Score: 0.9557, Raw Interest Score: 0.5904,
Positive Sentiment: 0.1398, Negative Sentiment 0.1088

Waltz: A Distributed Write-Ahead Log

stem and was generalized for broader use cases of distributed systems that require serializable consistency. Waltz is similar to existing log systems like Kafka in that it accepts/persists/propagates transaction data produced/consumed by many services. However, unlike other systems, Waltz provides a machinery that facilitates a serializable consistency in distributed applications. It detects conflicting transactions before they are committed to the log. Waltz is regarded as the single source of truth rather than the database, and it enables a highly reliable log-centric system architecture.


2019-09-09 07:00:00+00:00 Read the full story…
Weighted Interest Score: 0.8998, Raw Interest Score: 0.6180,
Positive Sentiment: 0.1681, Negative Sentiment 0.3144

Monitoring traffic of your Github repositories using Python and Google Cloud Platform — Part 1

Monitoring traffic of your Github repositories using Python and Google Cloud Platform — Part 1 Artem Rys Follow Sep 11 · 4 min read

Photo by Paweł Czerwiński on Unsplash

It is an article about monitoring your Github open-source repositories traffic. Unfortunately, you can see these statistics only by accessing each repository step by step. You may not want to access them at all… But if you do, you can use this small tool.

Technical stack:

2019-09-11 09:19:08.062000+00:00 Read the full story…
Weighted Interest Score: 0.8576, Raw Interest Score: 0.4656,
Positive Sentiment: 0.1225, Negative Sentiment 0.0490

What Remains Technical Breakdown

What Remains is a narrative adventure game for the 8-bit NES video game console, and was released in March 2019 as a free ROM, playable in emulator. It was created by a small team, Iodine Dynamics, over the course of two years of on and off development. It’s currently in the hardware phase as a limited batch of cartridges are being created from all recycled parts.

The game plays out over 6 stages, wherein the player walks around multiple scenes …
2019-09-10 00:00:00 Read the full story…
Weighted Interest Score: 0.7972, Raw Interest Score: 0.5335,
Positive Sentiment: 0.1656, Negative Sentiment 0.0981

Everything Apple announced at its 2019 iPhone event

Apple CEO Tim Cook took to the stage yesterday for the much-hyped By Innovation Only iPhone event — and, as expected, the Cupertino company unveiled more than a bunch of new smartphones.

Here’s a quick recap of everything Apple announced at the Steve Jobs Theater in Apple Park on Tuesday.


iPhone 11

After months of leaks and rumors, Apple finally unveiled its new baseline iPhone model — the iPhone 11. Similar to its predecessor, the iP…
2019-09-11 00:00:00 Read the full story…
Weighted Interest Score: 0.7860, Raw Interest Score: 0.5666,
Positive Sentiment: 0.0548, Negative Sentiment 0.0548

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