statmike / gcp-mlops
Google Cloud Platform Vertex AI end-to-end workflows for machine learning operations
statmike / gcp-mlops
google / edward2
A simple probabilistic programming language.
khalil-research / PyEPO
A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming
QInzhengk / Math-Model-and-Machine-Learning
数学建模和机器学习/深度学习/大模型的笔记和资料（持续更新中......）。
HenriquesLab / ZeroCostDL4Mic
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
CornellNLP / ConvoKit
ConvoKit is a toolkit for extracting conversational features and analyzing social phenomena in conversations. It includes several large conversational datasets along with scripts exemplifying the use of the toolkit on these datasets.
erdogant / bnlearn
Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inferences, Sampling methods.
giswqs / intro-gispro
Code examples for the book titled Introduction to GIS Programming
cfgranda / ps4ds
Probability and Statistics for Data Science: A self-contained introduction to probability and statistics for data science, including a free pdf, 103 Python notebooks using 23 real-world datasets, 118 videos with slides, and solutions to 200 exercises
huggingface / optimum-intel
🤗 Optimum Intel: Accelerate inference with Intel optimization tools
jMetal / jMetalPy
A framework for single/multi-objective optimization with metaheuristics
damian0815 / compel
A prompting enhancement library for transformers-type text embedding systems
EnoxSoftware / OpenCVForUnity
OpenCV for Unity (Untiy Asset Plugin)
joreilly / FantasyPremierLeague
Fantasy Premier League Kotlin/Compose Multiplatform sample
gyli / PyWaffle
🧇 Make Waffle Charts in Python.
abhisheks008 / DL-Simplified
Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013
Labellerr / Hands-On-Learning-in-Computer-Vision
Hands-On Learning in Computer Vision
LecterChu / nwpu-cram
西北工业大学/西工大/nwpu/npu软件学院复习(突击)资料！！
towardsai / ragbook-notebooks
Repository for the "Building LLMs for Production" book by Towards AI.
aws-samples / aws-ml-enablement-workshop
組織横断的にチームを組成し、機械学習による成長サイクルを実現する計画を立てるワークショップ
deepset-ai / haystack-cookbook
👩🏻🍳 A collection of example notebooks using Haystack
aws-samples / amazon-sagemaker-from-idea-to-production
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borglab / gtsfm
End-to-end SFM framework based on GTSAM
giswqs / geog-312
Introduction to GIS Programming
HayatoHongo / EveryonesLLM
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terrier-org / pyterrier
A Python framework for performing information retrieval experiments, building on http://terrier.org/
Kaggle / learntools
Tools and tests used in Kaggle Learn exercises
microsoft / Dynamics-365-FastTrack-Implementation-Assets
Dynamics 365 FastTrack Implementation guides
LukeDitria / pytorch_tutorials
Beginner Level Deep Learning Tutorials in Pytorch with Youtube Videos!
finic-ai / doctran
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IIC2233 / Syllabus
Repositorio principal del curso IIC2233 para el semestre 2026-2
DataFabric-Academy / ms-fabric-data-science
Hands-on Microsoft Fabric Data Science labs (FreshMart churn) with Thai study notes, PySpark/MLflow, and DP-604-aligned learning path.
wenqi9115-glitch / systematic-etf-relative-strength-alpha-attribution
Systematic ETF relative-strength research, overlapping-sleeve portfolio construction, LEAN implementation, and factor attribution.
IIC2233 / contenidos
Contenidos para el semestre 2026-2
Alif1642 / ai-traffic-violation-detection
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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.
leochlon / secant
RoPE attention is an exact forward-pass gradient step with softmax intact
imdigitalashish / gpt-from-scratch
A single executed notebook building and training a small GPT with RoPE and a phase-aware sparse MoE experiment
jaswantlhz / QGSS-26-Resources
Comprehensive archive of IBM Qiskit Global Summer School 2026 (QGSS '26) lecture slides, C++/Python lab walkthroughs, code notebooks, reading strategies, and a curated 80+ item Quantum Computing & QML resource collection.
semtm0051 / 2026_27
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LAPI-UNAM / quinta_escuela_de_computo_cuantico
En este repositorio se colocará el material utilizado durante la Quinta Escuela de Cómputo Cuántico.
carlosandreasa / meeting-minutes-generator
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Bennett-MLOps-Lab / SCSE3040-Lab
Lab Assignment Files
weltondionisio / USP_Redes_Neurais_Artificiais
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LosingLoonies-Youtube / congress-trading-investigation
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svhari / AAI_primer
Agentic AI Promer
GaTech-RL2 / EgoWAM
[CoRL 2026] EgoWAM: World Action Models Beyond Pixels with In-the-Wild Egocentric Human Data
NVDLI / fundamentals-of-deep-learning-zh
DLI Fundamentals of Deep Learning, Chinese Version
grongier / GeomodelingPython
A set of Jupyter notebooks to learn the basics of geological modeling in Python
YuyangLiu2003 / PRM-as-a-Judge
A practical toolkit for process-level robot evaluation with Process Reward Models (PRMs).
Harrypatria / Agentic-AI-Masterclass-Handbook-Usecases-Convergeni
Building AI agents and retrieval systems, a masterclass in LLM agents, RAG, and production deployment.
Neuradock / neuradock-eeg-101
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Ehsan-Roohi / FlowMLLab
Reproducible CFD-to-scientific-machine-learning experiments
teddylee777 / fastcampus-jev
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ArisuLoveASMR / ArisuLoveASMR
Ноутбук для Гугл коллаба, в котором вы сможете к абсолютно любому медиа добавить субтитры и автоматически их первести на любой язык
ro-witthawin / TBS-BI303-2026
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valbarriere / ECI2026_MModal_GenAI
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RajatDandekar / build-a-world-model-from-scratch
Build a World Model from Scratch — the Vizuara AI lecture series: slides, from-scratch code, and Colab notebooks
AnantVerma-2022 / KPMG_2_GLB
This repository contains the lecture materials, notebooks, code, datasets, assignments, demonstrations, and resources used during the Industry-Oriented AI Foundamentals Training Program conducted in August 2026.