alirezadir / AIMLInterviews

A study guide and interview-prep curriculum for AI/ML technical roles at big tech, covering coding, ML breadth, system design, and behavioral rounds.

higgsfield-ai / higgsfield

Open-source GPU cluster orchestrator and PyTorch-based framework for training LLMs with billions to trillions of parameters.

Exorust / TorchLeet

LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.

microsoft / FLAML

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

borglab / gtsam

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

google / brax

Massively parallel rigidbody physics simulation on accelerator hardware.

genieincodebottle / generative-ai

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

Akun-python / autumn-recruitment

Autumn-Recruit Algo Notes(秋招算法学习仓库)，面向大模型时代的算法、工程与AI学习共建仓库。从数学基础、数据结构，到机器学习、深度学习、LLM、Agent、AI-Infra、语音与数据科学，通过「理解→推导→手写 → 运行 → 验证 → 复盘构建可持续迭代的知识体系。

AkashSingh3031 / The-Complete-FAANG-Preparation

Dive into this repository, a comprehensive resource covering Data Structures, Algorithms, 450 DSA by Love Babbar, Striver DSA sheet, Apna College DSA Sheet, and FAANG Questions! 🚀 That's not all! We've got Technical Subjects like Operating Systems, DBMS, SQL, Computer Networks, and Object-Oriented Programming, all waiting for you.

ipython / ipyparallel

IPython Parallel: Interactive Parallel Computing in Python

AnswerDotAI / fastcore

Python supercharged for the fastai library

erdogant / bnlearn

Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.

IIC2233 / Syllabus

Repositorio principal del curso IIC2233 para el semestre 2026-2

shahidazam2020-oss / A-Comparative-Machine-Learning-Framework-for-Heart-Attack-Risk-Prediction-Using-Data-Preprocessing

This project presents a comparative machine learning framework for heart attack risk prediction using Python. It includes data preprocessing, feature engineering, SMOTE for class balancing, cross validation, and performance evaluation of multiple ML models.

RadixRootMind / RadixQuantVLA

RadixQuantVLA is a unified, Lego-like framework for post-training quantization, benchmarking, and deployment preparation of Vision-Language-Action models, integrating QuantVLA, Omega-QVLA, OpenVLA, UniVLA, StarVLA, GR00T, and Pi0.5 routes with standardized launchers and validation on LIBERO benchmarks.

IIC2233 / contenidos

Contenidos para el semestre 2026-2

Yunfan-Wang / Scalable-Agentic-Market-Simulator

SAMS - Scalable Agentic Market Simulator, a next gen AI finance automation paradigm, suitable for high frequency scenario while built for continuous learning and more sophisticated market simulation.

Prasannajaga / deployment-guide

Deployment & experimentation of LLM inference at production scale (P/D disaggregation, KV offloading, parallelism, and autoscaling).

AlexKrasnok / quantum-computing-lectures

Open quantum computing course for teaching, self-study, exam preparation, and quantum-technology career preparation.

yuxiangh383 / rl-interval-estimation

Multi-agent reinforcement learning in a macroeconomic environment, with V-learning and bootstrap confidence intervals for government policy parameters.

helvecioneto / datascience

Repositório para as aulas da disciplina SSIN0044 - INTRODUÇÃO À CIÊNCIA DE DADOS - T01 (Universidade Federal do Oeste do Pará)