Machine Learning in Finance: From Theory to Practice Book

Code repository for O'Reilly book

Quick, visual, principled introduction to pytorch code through five colab notebooks.

Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

Python code for part 2 of the book Causal Inference: What If, by Miguel Hernn and James Robins

Code, Notebooks and Examples from Practical Business Python

Notebooks for the “A walk with fastai2” Study Group and Lecture Series

The “Python Machine Learning (3rd edition)” book code repository