JupyterLab and Jupyter Notebooks

CloudQuant uses JuypterLab and Jupyter Notebooks in all of our data science projects. We find that this popular python environment with the standard and extended packages allow our internal and external quantitative analysts to create and share research that includes python code, equations, visualizations and research text. Our new CloudQuant.AI environment which is only available for internal users is built on JupyterLab. Watch for announcements from CloudQuant as we plan on opening this platform with our market data, fundamental data, and news/sentiment Alternative Datasets for registered crowd researchers.

The Jupyter Project is an open source project and can be found at http://jupyter.org/

Posts

Python Plotly Candlestick Chart with annonations

Candlestick Charts in Python with Plotly

Some traders are visually oriented. They need charts. As data scientists, we need to be able to present information in a way that others can understand. Presenting traders a candlestick chart is one of the best ways to transfer useful data. Blog Purpose: ✅ Demonstrate how to create a basic candlestick chart in Python 3 ✅ Demonstrate how to highlight/annotate points on the chart Topics covered in this post: Python, Plotly, OHLC, Candlestick Charts, Jupyter, Pandas, Traders
Numpy Memory Leak Fix

Fixing Python Memory Leaks

A few of our power users reported that long-running backtests would sometimes run out of memory. These power-users are the people who often find new trading strategies and so we wanted to work with them to improve the performance of our backtesting tools. Over the past couple of weeks, our senior engineer found that the problem wasn't in our code, but in one of the popular Python libraries that we use. We found the problem in numpy and numba. 
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JupyterLab and Notebook News. 25, October 2018

News clips about JupyterHub, JupyterLab, and Jupyter Notebooks provided algorithmically using our own Python application. This posting includes clips on JupyterHub with Kubernetes on OpenStack, Export Notebooks with nbConvert, Predicting the Stock Market, GOOG, MSFT...
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JupyterLab and Notebook News. 02, October 2018

JupyterLab-best open source software for data storage and analytics; Keys for Cloud-Based Machine Learning; San Diago workshop for Data Wrangling and Cleaning; Tutorial on Anaconda, NumPy and Pandas; Sleep Stage Classification; Set Up The AI Development Environment With Tensorflow, Exploratory Data Analysis; Chatbots
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Conversations: Learning Python within CloudQuant

What was your experience like learning Python within CloudQuant? We asked our portfolio managers and product management teammates who code in Python to explain their starting experiences in programming with Python with CloudQuant. We wanted to share with everyone what encouraged them to keep learning throughout the years. Everyone here codes as part of their job. This includes the CEO all the way down to the interns. We rely on our Backtesting Engine to ensure that trading algorithms work well before committing money to the automated trading strategies. But we also use JupyterLab in our daily work. We generate our reports, monitor our systems, and do all sorts of tasks in Python. Python has overtaken the spreadsheet in CloudQuant.
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JupyterLab and Notebook News. 08, June 2018

Looker Boosts Data Science Capabilities. Unsupervised Deep Learning Algorithms for Computer Vision. BlueData Introduces Turnkey Solution for AI and Machine Learning (including TensorFlow)
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AI & Machine Learning News. 28, May 2018

AI luggage, AI School Paper Grading, Importance of good data, Hybrid Data Management, Transcribe and Translate, 4 ML skills you won't learn in school, The one essential skill that will set you apart and a Beginner's Guide to Jupyter Notebooks.
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JupyterLab and Notebook News. 08, May 2018

News clips provided algorithmically. Anaconda's Damian Avila on the 2017 ACM Software System Award for Jupyter - Anaconda I am very happy to inform you that Project Jupyter has been awarded the 2017 ACM Software System Award! As…
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JupyterLab and Notebook News. 17, April 2018

CloudQuant has been using the beta version of JupyterLab for our internal portfolio managers in their research for Alpha Signals. This platform is very useful in for the data science portion of algorithm development. News related to JupyterLab and common data science toolkits used in Jupyter will appear in this periodic post from now on.
Trevor Trinkino Quantitative Trader

FXCM Machine Learning with Trevor Trinkino

On February 8th Trevor Trinkino presented Machine Learning with FXCM in a webinar. During this presentation, he promised to make available his machine learning Python Notebook and the supporting data file. These are available on our Google drive at: