An advanced course on LLMs offered at IIT Delhi by Prof. Tanmoy Chakraborty

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Repository of the Tranferlab Practical Anomaly Detection workshop

🏅 Collection of Kaggle Solutions and Ideas 🏅

Machine Learning Engineering Open Book

Anomaly detection related books, papers, videos, and toolboxes. Last update late 2025 for LLM and VLM works!

LLM101n: Let's build a Storyteller

A Library for Advanced Deep Time Series Models for General Time Series Analysis.

An intuitive library to extract features from time series.

A library to generate synthetic time series data by easy-to-use factors and generator

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

Pytorch implementation of "Light Schrödinger Bridge" (ICLR 2024)

Compiled variants of the Python standard library.

Official PyTorch implementation of TSDiff models presented in the NeurIPS 2023 paper "Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting"

Temporian is an open-source Python library for preprocessing ⚡ and feature engineering 🛠 temporal data 📈 for machine learning applications 🤖

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Conformal prediction for time-series applications.

Channel (Feature) selection for Multivariate Time series classification

Repo for AALTD Paper

Deep Learning Fundamentals -- Code material and exercises

A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python

a pyenv plugin to manage virtualenv (a.k.a. python-virtualenv)

Bayesian Data Analysis course at Aalto

STUMPY is a powerful and scalable Python library for modern time series analysis

Convert Machine Learning Code Between Frameworks

📺 Discover the latest machine learning / AI courses on YouTube.

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

Lecture notes and python code to replicate models built throughout the course of Richard Mcelreath's 2023 Lecture Series 'Statistical Rethinking'. Relies on pymc