chisras

spleeter

Deezer source separation library including pretrained models.

python-is-cool

Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.

imagededup

😎 Finding duplicate images made easy!

deeplearning-models

A collection of various deep learning architectures, models, and tips

Data-Science--Cheat-Sheet

Cheat Sheets

BentoML

The easiest way to serve AI apps and models - Build reliable Inference APIs, LLM apps, Multi-model chains, RAG service, and much more!

dabl

Data Analysis Baseline Library

tensorflow2.0-examples

Jupyter notebooks to help you started with tensorflow 2.0

MT-Reading-List

A machine translation reading list maintained by Tsinghua Natural Language Processing Group

pwc

This repository is no longer maintained.

NLP-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

homemade-machine-learning

🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

data-science-blogs

A curated list of data science blogs

pipeasy-spark

an easy way to define preprocessing data pipeline (similar to sklean-pandas but for Spark ML)

Surprise

A Python scikit for building and analyzing recommender systems

paiss_deeprl

Data-Science-Cheatsheet

probability_cheatsheet

A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.

content

Official content for Harvard CS109

Trend-Simpsons-Paradox

Random_Phenomena_by_Babatunde_Ogunnaike

📖 Solutions of exercises from the book "Random Phenomena: Fundamentals of Probability and Statistics for Engineers" by Babatunde Ogunnaike.

Repo-2017

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

private-ai-resources

SOON TO BE DEPRECATED - Private machine learning progress

gcForest

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

ML-From-Scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

LSTM_Networks

This is the code for "LSTM Networks - The Math of Intelligence (Week 8)" By Siraj Raval on Youtube

Machine-Learning-with-Python

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

Lessons-Learned-Data-Science-Interviews

Lessons learned the hard way through over 30+ data science interviews