Forwarded from Machine Learning with Python
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I'm sharing this link with my network once β and only the first 5 people who enroll through it lock in a deal that has never been offered before.
π Lifetime access to HelloEncyclo β every AI, ML & Data Science course ever built β for ~$41. Once. Forever.
This isn't a drill. This isn't a rerun.
This is the founding-member price β and it disappears the moment the first 250 seats globally are gone.
β 13 courses live right now
β 40+ more in 2β3 weeks
β Every future course included automatically
β 15-day money-back β full refund, no questions
Code: PRESALE-BOOK-WAVE-2GFG
(Log in with Gmail Β· valid once Β· applies at checkout)
π First 5. That's it.
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β€2
Forwarded from Machine Learning with Python
A new collection of free courses has been added:
π 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. π
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. π§
What's inside:
β’ Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
β’ A table with lectures, descriptions, videos, notes, and authors
β’ Links to the original lectures and accompanying notes
β’ WIP markers for incomplete materials
β’ Instructions for contributors on adding and improving notes
The idea was appreciated. π
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. πΊοΈ
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π 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. π
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. π§
What's inside:
β’ Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
β’ A table with lectures, descriptions, videos, notes, and authors
β’ Links to the original lectures and accompanying notes
β’ WIP markers for incomplete materials
β’ Instructions for contributors on adding and improving notes
The idea was appreciated. π
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. πΊοΈ
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - dair-ai/ML-Course-Notes: π Sharing machine learning course / lecture notes.
π Sharing machine learning course / lecture notes. - dair-ai/ML-Course-Notes
β€1
Stop studying LLM from random articles and videos that only explain individual pieces of the puzzle.
π LLM from Scratch β this is a practical course on PyTorch for those who want to understand the entire path of modern LLMs: from the first Transformer block to RLHF.
Instead of endless theory, here we gather a complete model training chain:
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πΉ Own training loop without Trainer magic: tokenization, batches, cross-entropy, validation loss, text generation
πΉ Modern architecture improvements: RMSNorm, RoPE, SwiGLU, KV Cache, sliding-window attention, and streaming cache
πΉ Full section on alignment: SFT, reward models, PPO-style RLHF, and GRPO with an analysis of how it looks in the training loop in practice
https://github.com/vivekkalyanarangan30/llm_from_scratch
#LLM #PyTorch #MachineLearning #DeepLearning #AI #Transformer
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π LLM from Scratch β this is a practical course on PyTorch for those who want to understand the entire path of modern LLMs: from the first Transformer block to RLHF.
Instead of endless theory, here we gather a complete model training chain:
πΉ Pretraining β Finetuning β Alignment in one course
πΉ Transformer from scratch: positional embeddings, self-attention, multi-head attention, MLP, residual connections, LayerNorm, and full Transformer blocks
πΉ Own training loop without Trainer magic: tokenization, batches, cross-entropy, validation loss, text generation
πΉ Modern architecture improvements: RMSNorm, RoPE, SwiGLU, KV Cache, sliding-window attention, and streaming cache
πΉ Full section on alignment: SFT, reward models, PPO-style RLHF, and GRPO with an analysis of how it looks in the training loop in practice
https://github.com/vivekkalyanarangan30/llm_from_scratch
#LLM #PyTorch #MachineLearning #DeepLearning #AI #Transformer
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€2
Media is too big
VIEW IN TELEGRAM
Join our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026.
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β Where do I start?
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If youβre interested in AI Engineering but unsure how to approach it, this livestream is for you.
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Sign up for FREE and save your seat here: luma.com/qgz4g4r7
Why should you join?
Many people interested in AI Engineering are asking the same questions:
β Where do I start?
π€ Do I need deep math first?
π§ Should I focus on ML, LLMs, RAG, or AI agents?
π§ How do I avoid wasting time learning the wrong things?
π How do I go from learning to becoming hireable?
If youβre interested in AI Engineering but unsure how to approach it, this livestream is for you.
What youβll learn
β¦ What AI Engineering really is
β¦ Where beginners should start
β¦ What skills and topics actually matter
β¦ Common mistakes to avoid
β¦ Self-study vs bootcamp vs MSc
β¦ How to think about becoming hireable in AI
β¦ Practical advice from someone already working in the field
Sign up for FREE and save your seat: luma.com/qgz4g4r7
β€5
Forwarded from Vinayak Chiluka
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At HelloEncyclo, we're building a comprehensive AI-powered learning platform designed to help students, professionals, and career switchers gain practical, industry-relevant skills through structured learning paths.
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π Exclusive Offer: Get FLAT 45% OFF on all courses using my referral link:
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π’ Stay updated with new course launches, discounts, learning resources, interview preparation tips, and career guidance:
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Whether you're preparing for your next job, aiming for a promotion, earning certifications, or simply upgrading your skills, HelloEncyclo is here to support
β€1
Forwarded from Machine Learning with Python
Agentic_Design_Patterns.pdf
19.2 MB
Agentic Design Patterns - a free 421-page document from a senior Google engineer. πβ¨
It's rare to find materials of such a large volume where the author doesn't try to sell a course after every chapter. π‘
Inside:
⬩ agent architectures
⬩ multi-agent systems
⬩ memory and context management
⬩ orchestration and task planning
⬩ tools, MCP, and integrations
⬩ production cases and code examples
#AgenticAI #LLM #GoogleEngineering #MultiAgentSystems #AIDevelopment #TechDocs
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
It's rare to find materials of such a large volume where the author doesn't try to sell a course after every chapter. π‘
Inside:
⬩ agent architectures
⬩ multi-agent systems
⬩ memory and context management
⬩ orchestration and task planning
⬩ tools, MCP, and integrations
⬩ production cases and code examples
#AgenticAI #LLM #GoogleEngineering #MultiAgentSystems #AIDevelopment #TechDocs
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€5
Forwarded from Machine Learning with Python
Kaggle and Google are launching a free 5-day intensive course on VibeCoding. π
Over five days, they will explain how agent-based coding works, how to configure skills, memory, and context, and how to make AI assistants not only useful but also safe. π€ The program includes daily tasks, live streams, discussions, and practical projects. π»
After completion, participants will receive an official certificate that can be added to their portfolio. π
Start date: June 15th. π
https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google π
If you've long wanted to properly understand agent-based coding, this is a great opportunity to dive in. π
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Over five days, they will explain how agent-based coding works, how to configure skills, memory, and context, and how to make AI assistants not only useful but also safe. π€ The program includes daily tasks, live streams, discussions, and practical projects. π»
After completion, participants will receive an official certificate that can be added to their portfolio. π
Start date: June 15th. π
https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google π
If you've long wanted to properly understand agent-based coding, this is a great opportunity to dive in. π
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Forwarded from Machine Learning with Python
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π Boosting AI agents for cybersecurity tasks
A huge collection of skills for AI agents focused on cybersecurity has been posted on GitHub.
It includes more than 750 skills: malware detection, certificate analysis, phishing detection, security audits, penetration testing, and many other tasks.
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
A huge collection of skills for AI agents focused on cybersecurity has been posted on GitHub.
It includes more than 750 skills: malware detection, certificate analysis, phishing detection, security audits, penetration testing, and many other tasks.
βοΈ Link to GitHub
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#AIAgents #CyberSecurity #MalwareDetection #InfoSec #TechNews #GitHub
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
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β€3
Forwarded from Machine Learning with Python
I often see people say that it's impossible to enter the IT field without expensive courses.
However, there's a huge amount of high-quality materials available for free:
π Computer Science
https://github.com/ossu/computer-science
π Data Structures & Algorithms
https://github.com/jwasham/coding-interview-university
π System Design
https://github.com/donnemartin/system-design-primer
π Web Development
https://github.com/TheOdinProject/curriculum
π Frontend / Backend / DevOps / Cloud
https://github.com/kamranahmedse/developer-roadmap
π Data Engineering
https://github.com/DataTalksClub/data-engineering-zoomcamp
π Machine Learning & AI
https://github.com/microsoft/ML-For-Beginners
π MLOps
https://github.com/DataTalksClub/mlops-zoomcamp
π Cybersecurity
https://github.com/OWASP/CheatSheetSeries
π Linux
https://github.com/trimstray/the-book-of-secret-knowledge
π Free Programming Books
https://github.com/EbookFoundation/free-programming-books
If you have internet and a bit of free time, you can learn computer science, algorithms, system design, DevOps, clouds, security, and machine learning for free.
The problem now isn't a lack of information. The problem is regularly opening these repositories and actually working on them.
#FreeLearning #ITCareer #CodingResources #TechEducation #OpenSource #DevCommunity
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
However, there's a huge amount of high-quality materials available for free:
π Computer Science
https://github.com/ossu/computer-science
π Data Structures & Algorithms
https://github.com/jwasham/coding-interview-university
π System Design
https://github.com/donnemartin/system-design-primer
π Web Development
https://github.com/TheOdinProject/curriculum
π Frontend / Backend / DevOps / Cloud
https://github.com/kamranahmedse/developer-roadmap
π Data Engineering
https://github.com/DataTalksClub/data-engineering-zoomcamp
π Machine Learning & AI
https://github.com/microsoft/ML-For-Beginners
π MLOps
https://github.com/DataTalksClub/mlops-zoomcamp
π Cybersecurity
https://github.com/OWASP/CheatSheetSeries
π Linux
https://github.com/trimstray/the-book-of-secret-knowledge
π Free Programming Books
https://github.com/EbookFoundation/free-programming-books
If you have internet and a bit of free time, you can learn computer science, algorithms, system design, DevOps, clouds, security, and machine learning for free.
The problem now isn't a lack of information. The problem is regularly opening these repositories and actually working on them.
#FreeLearning #ITCareer #CodingResources #TechEducation #OpenSource #DevCommunity
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - ossu/computer-science: π Path to a free self-taught education in Computer Science!
π Path to a free self-taught education in Computer Science! - ossu/computer-science
β€2
Google has published a free guide on scaling AI models and working with GPUs. π
π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
#AI #MachineLearning #GPU #Scaling #DeepLearning #Tech
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
#AI #MachineLearning #GPU #Scaling #DeepLearning #Tech
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
jax-ml.github.io
How To Scale Your Model
Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn't have to. This book aims to demystify the science of scaling language models: how TPUs (and GPUs) work and how they communicate with each otherβ¦
β€1
A large collection of materials on LLM Systems,
β’ model training (pre-training, RLHF, fault tolerance, stragglers)
β’ inference and serving
β’ agent systems
β’ edge deployment
β’ multimodal models
β’ technical reports from major laboratories
β’ reviews, benchmarks, and leaderboards
β’ courses on MLSys and collections of articles from conferences
https://github.com/AmberLJC/LLMSys-PaperList
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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https://github.com/AmberLJC/LLMSys-PaperList
#LLMSys #LLM #MachineLearning #AIResearch #DeepLearning #TechReports
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GitHub
GitHub - AmberLJC/LLMSys-PaperList: Large Language Model (LLM) Systems Paper List
Large Language Model (LLM) Systems Paper List. Contribute to AmberLJC/LLMSys-PaperList development by creating an account on GitHub.
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