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Handbook and recipes for data-driven solutions of real-world problems.

Documentation for Weights & Biases (Prompts), covering setup, features, and practical usage.

Documentation for Z.AI Developer Platform, covering setup, features, and practical usage.

Course materials and notes for Stanford class CS231n: Deep Learning for Computer Vision.

Supports teaching, studying or skills practice with AI-guided learning tools.

News, community, and courses for people building AI-powered products.

Visualizer for neural network, deep learning and machine learning models.

An educational resource designed to let anyone learn to become a skilled practitioner in deep reinforcement learning.

This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING].

Open-source project that provides machine-learning models, research, training resources, or evaluation tools.

Making neural nets uncool again, focused on making deep learning more accessible.

Discover open source deep learning code and pretrained models.

A flexible and efficient library for deep learning.

Helps find, analyze or synthesize information for research and knowledge discovery.

Cheaper V4 model, supports thinking and non-thinking modes.

Free and open source face recognition with deep neural networks.

Intelligent AI canvas for deep work, research, and learning.

Ranked Telegram bot #73 in the tgbotlist Top 100 quality directory.

Analyzes structured data and helps produce queries, insights or visualizations.

Paper by Dipankar Dasgupta, Deepak Venugopal and Kishor Datta Gupta.

Supports software work with AI-assisted coding, testing or application development.

DARPA research program that developed domain-specific search methods for hard-to-index web content.

Can you spot the DeepFake? Detect Fakes challenges you to discern AI-manipulated videos from real videos. Can you do better than an algorithm?

Dataset repository covering engineering, with searchable datasets.