Tunkara

Tunkara's Stars

• inkonchain/docs

  Ink Documentation

  Language:MDX28.6k297

• inkonchain/node

  How to run an Ink Node

  Language:Shell28.8k450

• inkonchain/ink-kit

  Onchain-focused SDK with ready-to-use templates, themes, and magical animated components ✨

  Language:TypeScript28.6k306

• unionlabs/union

  The trust-minimized, zero-knowledge bridging protocol, designed for censorship resistance, extremely high security, and usage in decentralized finance.

  Language:Rust14.6k922

• smolorg/smolgrad

  small auto-grad engine inspired from Karpathy's micrograd and PyTorch

  Language:Jupyter Notebook2328

• rasbt/LLMs-from-scratch

  Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

  Language:Jupyter Notebook38.3k5k

• ImagineAILab/ai-by-hand-excel

  2.4k354

• ml-tooling/best-of-ml-python

  🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

  18.9k2.6k

• gpu-mode/awesomeMLSys

  An ML Systems Onboarding list

  65621

• b7leung/MLE-Flashcards

  200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science.

  2k185

• jla524/fromthetensor

  From the Tensor to Stable Diffusion, a rough outline for a 1 week course.

  1k43

• practical-tutorials/project-based-learning

  Curated list of project-based tutorials

  214k27.9k

• karpathy/LLM101n

  LLM101n: Let's build a Storyteller

  31.1k1.7k

• maxim5/cs229-2018-autumn

  All notes and materials for the CS229: Machine Learning course by Stanford University

  Language:Jupyter Notebook2.1k857

• kjw0612/awesome-rnn

  Recurrent Neural Network - A curated list of resources dedicated to RNN

  6.1k1.4k

• dzyim/ilya-sutskever-recommended-reading

  It is said that, Ilya Sutskever gave John Carmack this reading list of ~ 30 research papers on deep learning.

  16423

• yzhao062/anomaly-detection-resources

  Anomaly detection related books, papers, videos, and toolboxes

  Language:Python8.5k1.8k

• donnemartin/data-science-ipython-notebooks

  Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  Language:Python27.8k7.9k

• GokuMohandas/Made-With-ML

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook38k6k

• kmario23/deep-learning-drizzle

  Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

  Language:HTML12.4k2.9k

• Spandan-Madan/DeepLearningProject

  An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

  Language:HTML4.8k637

• AssemblyAI-Community/Machine-Learning-From-Scratch

  Implementation of popular ML algorithms from scratch

  Language:Python795241

• gerdm/prml

  Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

  Language:Jupyter Notebook2.2k501

• naklecha/llama3-from-scratch

  llama3 implementation one matrix multiplication at a time

  Language:Jupyter Notebook14.1k1.1k

• Kiinitix/Malware-Detection-using-Machine-learning

  Anomaly based Malware Detection using Machine Learning (PE and URL)

  Language:Jupyter Notebook11444

• fastai/fastbook

  The fastai book, published as Jupyter Notebooks

  Language:Jupyter Notebook22.4k8.6k

• fastai/course22

  The fast.ai course notebooks

  Language:Jupyter Notebook2.6k1k

• SkalskiP/courses

  This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

  Language:Python5.6k510

• epogrebnyak/haskell-intro

  Seven classes on Haskell and a follow-up reading list

  Language:Haskell557

• codecrafters-io/build-your-own-x

  Master programming by recreating your favorite technologies from scratch.

  Language:Markdown328k30.4k