grahamjenson/list_of_recommender_systems: A List of Recommender Systems and Resources
A List of Recommender Systems and Resources. Contribute to grahamjenson/list_of_recommender_systems development by creating an account on GitHub.
rasbt/python-machine-learning-book-2nd-edition: The "Python Machine Learning (2nd edition)" book code repository and info resource
The "Python Machine Learning (2nd edition)" book code repository and info resource - rasbt/python-machine-learning-book-2nd-edition
neural networks#github#repositories#guides#neural#networks#AI/ML#deep#learning#data#science#scikit-learn#tensorflowsdmg15/Best-websites-a-programmer-should-visit: :link: Some useful websites for programmers.
:link: Some useful websites for programmers. Contribute to sdmg15/Best-websites-a-programmer-should-visit development by creating an account on GitHub.
CS#github#repositories#guides#cryptocurrency#CS#shell#script#interviews#career#MOOCs#AI/ML#C++#java#podcast#blogs#open-sourcekailashahirwar/cheatsheets-ai: Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5
Essential Cheat Sheets for deep learning and machine learning researchers https://medium.com/@kailashahirwar/essential-cheat-sheets-for-machine-learning-and-deep-learning-researchers-efb6a8ebd2e5 -...
neural networks#github#repositories#AI/ML#cheatsheets#deep#learning#R&D#numpy#keras#matplotlib#scipy#neural#networksageron/handson-ml3: A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2. - ageron/handson-ml3
neural networks#github#repositories#guides#AI/ML#notebooks#tensorflow#scikit-learn#keras#deep#learning#neural#networkslmoroney/dlaicourse: Notebooks for learning deep learning
Notebooks for learning deep learning. Contribute to lmoroney/dlaicourse development by creating an account on GitHub.
louisfb01/best_AI_papers_2021: A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code. - louisfb01/best_AI_papers_2021
neural networks#github#repositories#guides#AI/ML#papers#awesome#R&D#deep#learning#computer#vision#neural#networksdabochen/spreadsheet-is-all-you-need: A nanoGPT pipeline packed in a spreadsheet
A nanoGPT pipeline packed in a spreadsheet. Contribute to dabochen/spreadsheet-is-all-you-need development by creating an account on GitHub.
openai/gpt-3: GPT-3: Language Models are Few-Shot Learners
GPT-3: Language Models are Few-Shot Learners. Contribute to openai/gpt-3 development by creating an account on GitHub.
successfulstudy/promptoftheyear: In the evolving world of Large Language Models (LLMs), crafting effective prompts has become an essential skill. That's why I've created this collection, showcasing the most impactful prompts of the year across various intriguing domains. 🌐
In the evolving world of Large Language Models (LLMs), crafting effective prompts has become an essential skill. That's why I've created this collection, showcasing the most impactf...
microsoft/ML-For-Beginners: 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all - microsoft/ML-For-Beginners
ZuzooVn/machine-learning-for-software-engineers: A complete daily plan for studying to become a machine learning engineer.
A complete daily plan for studying to become a machine learning engineer. - ZuzooVn/machine-learning-for-software-engineers
zziz/pwc: This repository is no longer maintained.
This repository is no longer maintained. Contribute to zziz/pwc development by creating an account on GitHub.
d2l-ai/d2l-en: Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge. - d2l-ai/d2l-en
neural networks#github#repositories#guides#deep#learning#frameworks#math#AI/ML#data#science#NLP#computer#vision#reinforcement#pytorch#books#neural#networksaymericdamien/TensorFlow-Examples: TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2) - aymericdamien/TensorFlow-Examples
Avik-Jain/100-Days-Of-ML-Code: 100 Days of ML Coding
100 Days of ML Coding. Contribute to Avik-Jain/100-Days-Of-ML-Code development by creating an account on GitHub.
neural networks#github#repositories#guides#AI/ML#deep#learning#linear-regression#linear-algebra#scikit-learn#DSA#neural#networksGokuMohandas/Made-With-ML: Learn how to design, develop, deploy and iterate on production-grade ML applications.
Learn how to design, develop, deploy and iterate on production-grade ML applications. - GokuMohandas/Made-With-ML
neural networks#github#repositories#guides#AI/ML#production#data#science#NLP#deep#learning#LLM#neural#networksterryum/awesome-deep-learning-papers: The most cited deep learning papers
The most cited deep learning papers. Contribute to terryum/awesome-deep-learning-papers development by creating an account on GitHub.
yunjey/pytorch-tutorial: PyTorch Tutorial for Deep Learning Researchers
PyTorch Tutorial for Deep Learning Researchers. Contribute to yunjey/pytorch-tutorial development by creating an account on GitHub.
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.
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,...
neural networks#github#repositories#guides#data#science#python#notebooks#deep#learning#tensorflow#AI/ML#caffe#theano#spark#hadoop#numpy#scikit-learn#AWS#neural#networksgoogle/deepdream
Contribute to google/deepdream development by creating an account on GitHub.
endymecy/awesome-deeplearning-resources: Deep Learning and deep reinforcement learning research papers and some codes
Deep Learning and deep reinforcement learning research papers and some codes - endymecy/awesome-deeplearning-resources
neural networks#github#repositories#guides#AI/ML#deep#learning#papers#reinforcement#NLP#neural#networks#R&Drecommenders-team/recommenders: Best Practices on Recommendation Systems
Best Practices on Recommendation Systems. Contribute to recommenders-team/recommenders development by creating an account on GitHub.
ChristosChristofidis/awesome-deep-learning: A curated list of awesome Deep Learning tutorials, projects and communities.
A curated list of awesome Deep Learning tutorials, projects and communities. - ChristosChristofidis/awesome-deep-learning
openai/openai-cookbook: Examples and guides for using the OpenAI API
Examples and guides for using the OpenAI API. Contribute to openai/openai-cookbook development by creating an account on GitHub.
ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide: Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.
Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation. - ahmedbahaaeldin/From-0-to-Research-Scientist-resources-guide
neural networks#github#repositories#guides#scientist#AI/ML#deep#learning#calculus#linear-algebra#probability#R&D#neural#networkskarpathy/nn-zero-to-hero: Neural Networks: Zero to Hero
Neural Networks: Zero to Hero. Contribute to karpathy/nn-zero-to-hero development by creating an account on GitHub.
dair-ai/Prompt-Engineering-Guide: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering - dair-ai/Prompt-Engineering-Guide
neural networks#github#repositories#guides#AI/ML#prompt#engineering#deep#learning#openai#gen AI#neural#networksmicrosoft/generative-ai-for-beginners: 21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/ - microsoft/generative-ai-for-beginners