Forwarded from Data Analytics
The ultimate guide to fine tuning.pdf
15.2 MB
๐ The Big Book on Fine-Tuning LLMs
A free 115-page book dedicated to the retraining of large language models. ๐
It's suitable for those who want to understand how to prepare datasets, configure training, and improve the quality of LLMs for their tasks. ๐
#LLM #FineTuning #AI #MachineLearning #DataScience #Tech
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โ 13 courses live + 40+ coming soon
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๐ Use code: PRESALE-BOOK-WAVE-2GFG
๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
A free 115-page book dedicated to the retraining of large language models. ๐
It's suitable for those who want to understand how to prepare datasets, configure training, and improve the quality of LLMs for their tasks. ๐
#LLM #FineTuning #AI #MachineLearning #DataScience #Tech
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
๐ฏ One access, lifetime updates
๐ Use code: PRESALE-BOOK-WAVE-2GFG
๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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โ Free Resources:
ใปFree Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS courses: https://bit.ly/4alTSfk
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ใปIT Exams Skill Test: https://bit.ly/4dVPapB
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Data Science Interview Questions.pdf
1.4 MB
Data Science Interview Questions
๐ก Here is your curated list for Data Science interviews!
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๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
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๐ก Here is your curated list for Data Science interviews!
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โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
๐ฏ One access, lifetime updates
๐ Use code: PRESALE-BOOK-WAVE-2GFG
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I'm sharing this link with my network once โ and only the first 5 people who enroll through it lock in a deal that has never been offered before.
๐ Lifetime access to HelloEncyclo โ every AI, ML & Data Science course ever built โ for ~$41. Once. Forever.
This isn't a drill. This isn't a rerun.
This is the founding-member price โ and it disappears the moment the first 250 seats globally are gone.
โ 13 courses live right now
โ 40+ more in 2โ3 weeks
โ Every future course included automatically
โ 15-day money-back โ full refund, no questions
Code: PRESALE-BOOK-WAVE-2GFG
(Log in with Gmail ยท valid once ยท applies at checkout)
๐ First 5. That's it.
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โณ Once those 5 seats go through this link โ
I'm not sharing it again. ๐ฅ
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A new collection of free courses has been added:
๐ 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. ๐
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. ๐ง
What's inside:
โข Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
โข A table with lectures, descriptions, videos, notes, and authors
โข Links to the original lectures and accompanying notes
โข WIP markers for incomplete materials
โข Instructions for contributors on adding and improving notes
The idea was appreciated. ๐
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. ๐บ๏ธ
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
๐ฏ One access, lifetime updates
๐ Use code: PRESALE-BOOK-WAVE-2GFG
๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
๐ 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. ๐
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. ๐ง
What's inside:
โข Courses from the Machine Learning Specialization, MIT 6.S191, CMU Neural Nets for NLP, CS224N, CS25, and others
โข A table with lectures, descriptions, videos, notes, and authors
โข Links to the original lectures and accompanying notes
โข WIP markers for incomplete materials
โข Instructions for contributors on adding and improving notes
The idea was appreciated. ๐
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. ๐บ๏ธ
#MachineLearning #AI #DataScience #TechCommunity #LearningResources #OpenSource
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
โญ๏ธ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
๐ฏ One access, lifetime updates
๐ Use code: PRESALE-BOOK-WAVE-2GFG
๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
GitHub
GitHub - dair-ai/ML-Course-Notes: ๐ Sharing machine learning course / lecture notes.
๐ Sharing machine learning course / lecture notes. - dair-ai/ML-Course-Notes
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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:
โ Where do I start?
๐ค Do I need deep math first?
๐ง Should I focus on ML, LLMs, RAG, or AI agents?
๐งญ How do I avoid wasting time learning the wrong things?
๐ How do I go from learning to becoming hireable?
If youโre interested in AI Engineering but unsure how to approach it, this livestream is for you.
What youโll learn
โฆ What AI Engineering really is
โฆ Where beginners should start
โฆ What skills and topics actually matter
โฆ Common mistakes to avoid
โฆ Self-study vs bootcamp vs MSc
โฆ How to think about becoming hireable in AI
โฆ Practical advice from someone already working in the field
Sign up for FREE and save your seat: luma.com/qgz4g4r7
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5 Fun Papers That Explain LLMs Clearly ๐โจ
Want to understand LLMs better? Start with these five foundational papers that explain how they work. ๐ค
Large language models (LLMs) can feel complicated at first. There are transformers, attention layers, scaling laws, pretraining, instruction tuning, human feedback, retrieval, and many other ideas around them. ๐ง But the best way to understand large language models is not to start with a huge textbook. A better way is to read a few important papers that each explain one major part of the system. ๐ This article is part of a fun series where we learn by exploring core ideas, practical projects, and the research papers behind modern technology. ๐ฌ In this article, we will go through five papers that explain how LLMs work. So, let's get started. ๐
More: https://www.kdnuggets.com/5-fun-papers-that-explain-llms-clearly
#LLM #AI #MachineLearning #DeepLearning #DataScience #Tech
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๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
๐ฏ One access, lifetime updates
๐ Use code: PRESALE-BOOK-WAVE-2GFG
๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Want to understand LLMs better? Start with these five foundational papers that explain how they work. ๐ค
Large language models (LLMs) can feel complicated at first. There are transformers, attention layers, scaling laws, pretraining, instruction tuning, human feedback, retrieval, and many other ideas around them. ๐ง But the best way to understand large language models is not to start with a huge textbook. A better way is to read a few important papers that each explain one major part of the system. ๐ This article is part of a fun series where we learn by exploring core ideas, practical projects, and the research papers behind modern technology. ๐ฌ In this article, we will go through five papers that explain how LLMs work. So, let's get started. ๐
More: https://www.kdnuggets.com/5-fun-papers-that-explain-llms-clearly
#LLM #AI #MachineLearning #DeepLearning #DataScience #Tech
โจ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
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๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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๐ Level up your AI & Data Science skills with HelloEncyclo โ a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
โ 13 courses live + 40+ coming soon
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๐ https://helloencyclo.com/?ref=HUSSEINSHEIKHO
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