12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

Deep Learning for humans

💫 Industrial-strength Natural Language Processing (NLP) in Python

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Low-code framework for building custom LLMs, neural networks, and other AI models

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

Fast and Accurate ML in 3 Lines of Code

Data science interview questions and answers

12 Weeks, 24 Lessons, AI for All!

Google Research

A Python library for anomaly detection across tabular, time series, graph, text, and image data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

A python library for user-friendly forecasting and anomaly detection on time series.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.