└── README.md /README.md: -------------------------------------------------------------------------------- 1 | [![HitCount](http://hits.dwyl.com/kannansingaravelu/PythonResources.svg)](http://hits.dwyl.com/kannansingaravelu/PythonResources) 2 | # PythonResources 3 | My curated list of resources on Data Science, Machine Learning, and Quantitative Finance. This is not an exhaustive list but helps you get started. 4 | 5 | --- 6 | 7 | 8 | ### Data API 9 | 10 | - [Alphavantage](https://github.com/RomelTorres/alpha_vantage) - Python module to get stock data from the Alpha Vantage API. 11 | 12 | - [Bloomberg Open API](https://github.com/MatthewGilbert/pdblp) - Bloomberg Open API with pandas. 13 | 14 | - [Eikon Data API](https://developers.refinitiv.com/eikon-apis/eikon-data-api) - Python package for retrieving Eikon data. 15 | 16 | - [IEX](https://github.com/addisonlynch/iexfinance) - Python module to get stock data from IEX Cloud and IEX API 1.0. 17 | 18 | - [TWS API](https://interactivebrokers.github.io/tws-api/introduction.html) - Interactive Brokers interface to retrieve data and automate trading strategies. 19 | 20 | - [YFinance](https://github.com/ranaroussi/yfinance) - Yahoo! Finance market data downloader. 21 | 22 | ### Data Science & Machine Learning 23 | 24 | - [Aurelien Geron (2019), Hands–On Machine Learning with Scikit–Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems](https://amzn.to/3hMNeSD) 25 | 26 | - [François Chollet (2017), Deep Learning with Python](https://amzn.to/3dgeu8t) 27 | 28 | - [Jake VanderPlas (2016), Data Science Handbook: Essential Tools for Working with Data](https://amzn.to/3hNDIP5) 29 | 30 | - [Marcos M. Lopez de Prado (2020), Machine Learning for Asset Managers (Elements in Quantitative Finance)](https://amzn.to/3dfQBOs) 31 | 32 | - [Tony Guida (2019), Big Data and Machine Learning in Quantitative Investment](https://amzn.to/2V5dqy7) 33 | 34 | - [Yves Hilpisch (2020), Artificial Intelligence in Finance: A Python–based Guide](https://amzn.to/2BmcbDH) 35 | 36 | 37 | ### Derivatives 38 | 39 | - [Yves Hilpisch (2015), Derivatives Analytics with Python: Data Analysis, Models, Simulation, Calibration and Hedging](https://amzn.to/2V59QnF) 40 | 41 | - [Yves Hilpisch (2016), Listed Volatility and Variance Derivatives: A Python–based Guide](https://amzn.to/3fPxvk5) 42 | 43 | - [QuantLib-Python](https://www.quantlib.org) - Backward-compatible meta-package for the QuantLib module. 44 | 45 | 46 | ### Numerical Libraries 47 | 48 | - [Keras](https://github.com/keras-team/keras) - Keras is a high-level neural networks API for Python. 49 | 50 | - [NumPy](http://www.numpy.org) - Fundamental package for array computing with Python. 51 | 52 | - [Pandas](http://pandas.pydata.org) - Powerful data structures for data analysis, time series, and statistics. 53 | 54 | - [Scikit-Learn](https://scikit-learn.org/stable) - Python modules for machine learning and data mining. 55 | 56 | - [SciPy](https://www.scipy.org) - Scientific Library for Python. 57 | 58 | - [TensorFlow](https://www.tensorflow.org) - Open source library for high performance numerical computation. 59 | 60 | 61 | ### Python 62 | 63 | - [Wes McKinney (2018), Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython](https://amzn.to/2AYvQtB) 64 | 65 | - [Yves Hilpisch (2018), Python for Finance: Mastering Data-Driven Finance](https://amzn.to/311RSGr) 66 | 67 | 68 | ### Technical Analysis Libraries 69 | 70 | - [TA-Lib](https://github.com/mrjbq7/ta-lib) - Python wrapper for TA-Lib 71 | - [Pandas-ta](https://github.com/twopirllc/pandas-ta) - Easy to use technical analysis library 72 | 73 | 74 | ### Validation Libraries 75 | 76 | - [Backtrader](https://github.com/mementum/backtrader) - A feature-rich Python framework for backtesting and trading. 77 | 78 | 79 | ### Visualization Libraries 80 | 81 | - [Bokeh](http://github.com/bokeh/bokeh) - Interactive visualization library for modern web browsers. 82 | 83 | - [BQPlot](https://github.com/bqplot/bqplot) - Interactive plotting for the Jupyter notebook, using D3.js and IPywidgets. 84 | 85 | - [Cufflinks](https://github.com/santosjorge/cufflinks) -  Productivity Tools for Plotly + Pandas. 86 | 87 | - [IPywidgets](https://ipywidgets.readthedocs.io/en/latest) - Interactive HTML widgets for Jupyter notebooks and the IPython kernel. 88 | 89 | - [Matplotlib](https://matplotlib.org) - Comprehensive library for creating static, animated, and interactive visualizations in Python. 90 | 91 | - [Plotly](https://plotly.com/python/) - Open-source, interactive data visualization library for Python 92 | 93 | - [Seaborn](https://seaborn.pydata.org) - Library for making statistical graphics in Python. 94 | 95 | 96 | ### Wheels 97 | 98 | - [Python Wheels](https://pythonwheels.com) - New standard of Python distribution. 99 | 100 | --------------------------------------------------------------------------------