The complete code and notebooks used for the ACM Recommender Systems Challenge 2019

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Colab Compatible FastAI notebooks for NLP and Computer Vision Datasets

Learning PyTorch through the D2L book. A series of notebooks for the same

A notebook of awesome privacy protection,federated learning, fairness and blockchain research materials.

Data Science portfolio of ipython Notebooks with several Machine Learning algorithms. They follow a structured data science methodology to face various challenges

Machine learning Python notebooks based on the ML Course assignments

Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay

This repository houses 3 different Jupyter Notebooks that each analyze the similarity in data points to most effectively inform customer recommendations in the retail space.

This repository contains a collection of machine learning models and notebooks, primarily focused on the housing dataset. It includes implementations of linear regression, logistic regression, feature scaling techniques, and gradient descent using scikit-learn. Additionally, it features learnings from the University of Washington's ML Specializatio