Learn how to design, develop, deploy and iterate on production-grade ML applications.

A game theoretic approach to explain the output of any machine learning model.

The fastai book, published as Jupyter Notebooks

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

Tutorials for creating and using ONNX models

This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative ski…

Efficient few-shot learning with Sentence Transformers

Machine Learning in Asset Management (by @firmai)

Code / solutions for Mathematics for Machine Learning (MML Book)

Python/PyMC3 versions of the programs described in Doing bayesian data analysis by John K. Kruschke

A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.