Discover the Best AI Resources

FaceSwap (deepfakes/faceswap)

Swaps faces in images and videos using deep learning, offering tools to extract faces, train generative models, and convert media via CLI or GUI for research, VFX, and ethical experimentation.

Streamlit

Turns a top-to-bottom Python script into an interactive web app: each widget interaction reruns the whole script, with cache decorators skipping redundant work. No callbacks or HTML needed; built for data dashboards, ML demos, and internal tools.

GLUE (General Language Understanding Evaluation benchmark)

A multi-task English NLU benchmark for evaluating models across nine tasks (acceptability, sentiment, paraphrase, similarity, and various NLI setups), with a diagnostic evaluation set and an online leaderboard to compare generalization and transfer learning.

build-your-own-x

Curates step-by-step, hands-on tutorials for reimplementing technologies from scratch—covering everything from OSs and compilers to neural networks, LLMs, and vision systems—so learners learn by rebuilding real systems across languages.

ML for Trading — 2nd Edition

Provides 150+ executed Jupyter notebooks and code that reproduce the book 'Machine Learning for Algorithmic Trading (2nd ed.)' — covers feature engineering, alternative-data signal extraction, backtesting, NLP, deep learning and reinforcement learning for trading; best for quant researchers and practitioners.

Embeds multi-head self-attention inside an LSTM-style memory, so stored memories can attend to one another instead of just sitting in separate slots — sharpening relational reasoning and topping WikiText-103, Project Gutenberg, and GigaWord.

MLflow

Tracks ML and LLM experiments end to end: logs params, metrics, and artifacts, versions models in a registry, and records agent traces via OpenTelemetry. Framework-agnostic, runs locally or self-hosted, with 50+ built-in evaluation metrics and LLM judges.

Introduced the two-stage recipe behind the GPT lineage: unsupervised generative pre-training on unlabeled text, then supervised fine-tuning per task. A single 12-layer Transformer decoder beat bespoke architectures on 9 of 12 NLP benchmarks.

NautilusTrader

Rust-native, event-driven trading platform for backtesting and live execution across crypto, forex, equities, and futures on 27+ venues. The same strategy code runs in nanosecond backtests and in production, giving true research-to-live parity.

Prefect

Orchestrates and schedules Python data pipelines and workflows with primitives for retries, caching, parameters, and deployments. Provides either a self-hosted server or managed Prefect Cloud for monitoring, observability, and integrations across common data tools.

Machine Learning cheatsheets for Stanford's CS 229

Condenses Stanford's CS 229 into one-page visual cheatsheets spanning supervised, unsupervised, and deep learning, plus probability and linear-algebra refreshers. Available in 10+ languages, with all topics merged into one Super VIP PDF.

Kornia

Brings classic computer vision into PyTorch as differentiable, GPU-accelerated tensor operators — filters, geometric transforms, feature matching, camera calibration — so each step lives inside autograd and trains end-to-end with neural networks.