kannansingaravelu/PythonResources

My curated list of resources on Data Science, Machine Learning, and Quantitative Finance

PythonResources

My curated list of resources on Data Science, Machine Learning, and Quantitative Finance. This is not an exhaustive list but helps you get started.

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Data API

• Alphavantage - Python module to get stock data from the Alpha Vantage API.

• Bloomberg Open API - Bloomberg Open API with pandas.

• Eikon Data API - Python package for retrieving Eikon data.

• IEX - Python module to get stock data from IEX Cloud and IEX API 1.0.

• TWS API - Interactive Brokers interface to retrieve data and automate trading strategies.

• YFinance - Yahoo! Finance market data downloader.

Data Science & Machine Learning

• Aurelien Geron (2019), Hands–On Machine Learning with Scikit–Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

• François Chollet (2017), Deep Learning with Python

• Jake VanderPlas (2016), Data Science Handbook: Essential Tools for Working with Data

• Marcos M. Lopez de Prado (2020), Machine Learning for Asset Managers (Elements in Quantitative Finance)

• Tony Guida (2019), Big Data and Machine Learning in Quantitative Investment

• Yves Hilpisch (2020), Artificial Intelligence in Finance: A Python–based Guide

Derivatives

• Yves Hilpisch (2015), Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging

• Yves Hilpisch (2016), Listed Volatility and Variance Derivatives: A Python–based Guide

• QuantLib-Python - Backward-compatible meta-package for the QuantLib module.

Numerical Libraries

• Keras - Keras is a high-level neural networks API for Python.

• NumPy - Fundamental package for array computing with Python.

• Pandas - Powerful data structures for data analysis, time series, and statistics.

• Scikit-Learn - Python modules for machine learning and data mining.

• SciPy - Scientific Library for Python.

• TensorFlow - Open source library for high performance numerical computation.

Python

• Wes McKinney (2018), Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

• Yves Hilpisch (2018), Python for Finance: Mastering Data-Driven Finance

Technical Analysis Libraries

• TA-Lib - Python wrapper for TA-Lib
• Pandas-ta - Easy to use technical analysis library

Validation Libraries

• Backtrader - A feature-rich Python framework for backtesting and trading.

Visualization Libraries

• Bokeh - Interactive visualization library for modern web browsers.

• BQPlot - Interactive plotting for the Jupyter notebook, using D3.js and IPywidgets.

• Cufflinks -  Productivity Tools for Plotly + Pandas.

• IPywidgets - Interactive HTML widgets for Jupyter notebooks and the IPython kernel.

• Matplotlib - Comprehensive library for creating static, animated, and interactive visualizations in Python.

• Plotly - Open-source, interactive data visualization library for Python

• Seaborn - Library for making statistical graphics in Python.

Wheels

• Python Wheels - New standard of Python distribution.