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devkodeio/the-dom-challenge: DOM Challenge is a 60-90 minutes online weekly challenge related to frontend development consisting of industrial level machine round questions.
devkodeio/the-dom-challenge: DOM Challenge is a 60-90 minutes online weekly challenge related to frontend development consisting of industrial level machine round questions.
DOM Challenge is a 60-90 minutes online weekly challenge related to frontend development consisting of industrial level machine round questions. - devkodeio/the-dom-challenge
·github.com·
devkodeio/the-dom-challenge: DOM Challenge is a 60-90 minutes online weekly challenge related to frontend development consisting of industrial level machine round questions.
kailashahirwar/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
kailashahirwar/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 -...
·github.com·
kailashahirwar/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
ageron/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.
ageron/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
·github.com·
ageron/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.
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.
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
·github.com·
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.
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. 🌐
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...
·github.com·
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. 🌐
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.
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
·github.com·
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.