Applied Machine Learning in Python: a Hands-on Guide with Code 🧠
🚀 Exciting news! free, online e-book has been updated with fresh theory 📕 , detailed illustrations 🎨 , well-documented demos 📝 , links to YouTube lectures 🎥, and interactive dashboards 📊 !
Each chapter is downloadable📥 , making it easy for you to dive in, learn, and complete your #DataScience projects efficiently! 🧑💻
Explore it now: https://geostatsguy.github.io/MachineLearningDemos_Book/intro.html
#DeepLearning #Python #MachineLearning #AI #DataAnalytics #TechEducation #FreeLearning #Ebook #DataVisualization #Coding #STEM #TechCommunity #LearnToCode
https://t.iss.one/CodeProgrammer
Each chapter is downloadable
Explore it now: https://geostatsguy.github.io/MachineLearningDemos_Book/intro.html
#DeepLearning #Python #MachineLearning #AI #DataAnalytics #TechEducation #FreeLearning #Ebook #DataVisualization #Coding #STEM #TechCommunity #LearnToCode
https://t.iss.one/CodeProgrammer
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🚀 Thrilled to announce a major milestone in our collective upskilling journey! 🌟
I am incredibly excited to share a curated ecosystem of high-impact resources focused on Machine Learning and Artificial Intelligence. By consolidating a comprehensive library of PDFs—from foundational onboarding to advanced strategic insights—into a single, unified repository, we are effectively eliminating search friction and accelerating our learning velocity. 📚✨
This initiative represents a powerful opportunity to align our technical growth with future-ready priorities, ensuring we are always ahead of the curve. 💡🔗
⛓️ Unlock your potential here:
https://github.com/Ramakm/AI-ML-Book-References
#MachineLearning #AI #ContinuousLearning #GrowthMindset #TechCommunity #OpenSource
I am incredibly excited to share a curated ecosystem of high-impact resources focused on Machine Learning and Artificial Intelligence. By consolidating a comprehensive library of PDFs—from foundational onboarding to advanced strategic insights—into a single, unified repository, we are effectively eliminating search friction and accelerating our learning velocity. 📚✨
This initiative represents a powerful opportunity to align our technical growth with future-ready priorities, ensuring we are always ahead of the curve. 💡🔗
⛓️ Unlock your potential here:
https://github.com/Ramakm/AI-ML-Book-References
#MachineLearning #AI #ContinuousLearning #GrowthMindset #TechCommunity #OpenSource
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Awesome DataScience — a structured list of open-source data, datasets, libraries, and tutorials for solving real-world problems. 🛠️
It's useful for both beginners and those already familiar with the field — you'll find something new here.
⛓️ Link to GitHub: https://github.com/academic/awesome-datascience
tags: #DataScientist
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A new collection of free courses has been added:
🔗 https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠
What's inside:
• Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
• A table with lectures, descriptions, videos, notes, and authors
• Links to the original lectures and accompanying notes
• WIP markers for incomplete materials
• Instructions for contributors on adding and improving notes
The idea was appreciated. 👍
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
✨ Join Best TG Channels https://t.iss.one/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
🔗 https://github.com/dair-ai/ML-Course-Notes
Those studying ML through dozens of random tabs and unclosed playlists may find this repository useful for organizing their learning. 📚
Machine Learning Course Notes is an open collection of notes on machine learning, NLP, and AI, compiled around full-fledged courses, not just individual videos. 🧠
What's inside:
• Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
• A table with lectures, descriptions, videos, notes, and authors
• Links to the original lectures and accompanying notes
• WIP markers for incomplete materials
• Instructions for contributors on adding and improving notes
The idea was appreciated. 👍
Instead of another collection of hundreds of links, a course map has been created where one can systematically go through the material without getting lost after a week of studying. 🗺️
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
✨ Join Best TG Channels https://t.iss.one/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - dair-ai/ML-Course-Notes: 🎓 Sharing machine learning course / lecture notes.
🎓 Sharing machine learning course / lecture notes. - dair-ai/ML-Course-Notes
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