you don’t need random tutorials to learn llms.
this course teaches you from fundamentals to deployment.
3 parts. 1 complete llm skillset.
llm fundamentals
/mathematics for machine Learning
/python for machine Learning
/neural networks
/natural language processing (nlp)
the https://t.co/7Kstkm5iDw
this course teaches you from fundamentals to deployment.
3 parts. 1 complete llm skillset.
llm fundamentals
/mathematics for machine Learning
/python for machine Learning
/neural networks
/natural language processing (nlp)
the https://t.co/7Kstkm5iDw
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90% of deep learning projects start with pytorch.
but most beginners get stuck because:
> they skip the basics
> jump straight into building models
master the pytorch fundamentals step by step:
> with clear explanations
> hands-on code
/What are tensors
/tensor Initialization https://t.co/bfqdaT0nYs
but most beginners get stuck because:
> they skip the basics
> jump straight into building models
master the pytorch fundamentals step by step:
> with clear explanations
> hands-on code
/What are tensors
/tensor Initialization https://t.co/bfqdaT0nYs
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collection of 300 ml system design case studies.
from over 80 leading companies.
apple, amazon, microsoft, meta, etc.
practical examples of ml system design.
/real world applications.
/clear insights you can learn from.
case studies across industries.
/tech.
/finance. https://t.co/Wp6lwXzsd5
from over 80 leading companies.
apple, amazon, microsoft, meta, etc.
practical examples of ml system design.
/real world applications.
/clear insights you can learn from.
case studies across industries.
/tech.
/finance. https://t.co/Wp6lwXzsd5
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Best YouTube channels for Linear Algebra https://t.co/PuUpoCmup9
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the only LLM cheatsheet you’ll ever need.
covers concepts, architectures, and applications.
> foundations
tokens
tokenizer
bpe
embeddings
cosine similarity
attention
attention formula
multi head attention
> transformers architecture and variants
bert
encoder only models https://t.co/C8KIkN8PmJ
covers concepts, architectures, and applications.
> foundations
tokens
tokenizer
bpe
embeddings
cosine similarity
attention
attention formula
multi head attention
> transformers architecture and variants
bert
encoder only models https://t.co/C8KIkN8PmJ
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this playlist has 26 deep learning lectures.
one of the best free resources online.
go from beginner to confident in just 5 hours. https://t.co/3kZPtTO3a3
one of the best free resources online.
go from beginner to confident in just 5 hours. https://t.co/3kZPtTO3a3
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3 valid reasons to train your own LLM. if yours is not listed, stop now.
if you cannot answer "WHY" in one sentence, you probably should "NOT" train an LLM.
a team gets access to GPUs. the thought is simple.
we have compute. let’s train an LLM. six months later, the LLM is https://t.co/O4pkoDudr1
if you cannot answer "WHY" in one sentence, you probably should "NOT" train an LLM.
a team gets access to GPUs. the thought is simple.
we have compute. let’s train an LLM. six months later, the LLM is https://t.co/O4pkoDudr1
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deep learning is not scary.
when you have the best youtube playlist.
master deep learning step by step:
> from the basics to advanced
> with clear explanations https://t.co/fo7ibWzOLE
when you have the best youtube playlist.
master deep learning step by step:
> from the basics to advanced
> with clear explanations https://t.co/fo7ibWzOLE
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#100DayChallenge Day 5 of posting something interesting I learn every day (credits to @real_deep_ml for this one). The Compressed Sparse Row (CSR) format is an efficient representation of sparse matrices, which predominantly have zero entries. (1/n) https://t.co/YUzazcYmDT
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15 important genai ideas made simple.
covers the concepts you can’t skip .
> transformer
> large language model (llms)
> tokenization
> attention
> fine tuning
> few shot prompting
> retrieval augmented generation (rag)
> vector database
> agents
> model context protocol (mcp) https://t.co/Rm08zLX3mb
covers the concepts you can’t skip .
> transformer
> large language model (llms)
> tokenization
> attention
> fine tuning
> few shot prompting
> retrieval augmented generation (rag)
> vector database
> agents
> model context protocol (mcp) https://t.co/Rm08zLX3mb
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looks great, right?
(was testing something) https://t.co/JSTf6wnvS0
(was testing something) https://t.co/JSTf6wnvS0
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mit literally packed 7 hours with everything.
you need to know about genai for free.
https://t.co/VRFSQM6s2C https://t.co/UB5t992DcX
you need to know about genai for free.
https://t.co/VRFSQM6s2C https://t.co/UB5t992DcX
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want to ace your next llm interview?
find top 50 llm interview questions.
covers the topics you can’t skip.
grab here: https://t.co/Q5UfhHN2mA https://t.co/Xvo19NtffE
find top 50 llm interview questions.
covers the topics you can’t skip.
grab here: https://t.co/Q5UfhHN2mA https://t.co/Xvo19NtffE
1
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Amazon has 1,000+ AI/ML books. But these 9 cover 99% of everything you need to know. https://t.co/fkb08zs9NZ
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a google engineer dropped agentic design patterns.
this isn’t a blog post.
It’s a curriculum.
and it’s free.
> 400+ pages packed with patterns, code, and design insights.
> this is one of the most practical, hands-on resources for anyone serious about building real systems https://t.co/Smr8PkgGvf
this isn’t a blog post.
It’s a curriculum.
and it’s free.
> 400+ pages packed with patterns, code, and design insights.
> this is one of the most practical, hands-on resources for anyone serious about building real systems https://t.co/Smr8PkgGvf
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this 185-page book unlocks the secrets of deep learning.
Download here: https://t.co/kNZoncHtdl https://t.co/nirHmNQl5d
Download here: https://t.co/kNZoncHtdl https://t.co/nirHmNQl5d
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90% of deep learning projects start with pytorch.
but most beginners get stuck because:
> they skip the basics
> jump straight into building models
master the pytorch fundamentals step by step:
> with clear explanations
> hands on code https://t.co/OyKJIoCiK2
but most beginners get stuck because:
> they skip the basics
> jump straight into building models
master the pytorch fundamentals step by step:
> with clear explanations
> hands on code https://t.co/OyKJIoCiK2
2
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these 9 lectures from MIT on Generative AI are pure goldmine. https://t.co/hI2Yd52WJK
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this guy literally explained antigravity in 33 mins.
https://t.co/PUJT49ltxm
https://t.co/PUJT49ltxm
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> best LLMs cheatsheet you’ll ever find.
> covers concepts, finetuning, evaluations.
https://t.co/uVNLB1Uqug https://t.co/5o3li4Psyu
> covers concepts, finetuning, evaluations.
https://t.co/uVNLB1Uqug https://t.co/5o3li4Psyu
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Simplifying LLMs, Al Agents, RAGs and ML for you! | Sr. Data Scientist | A Decade of Experience | Creator of AwesomeNeuron
2.8K Followers
17 Contributions
AI/ML/DL and a sprinkle of DSA. Prev: ML @dynamo_ai (YC W22), @RutgersU; Research @iitroorkee, @UWAR_Lab
15 Followers
1 Contributions
19 | self taught AI Engineer | love math | i am a dumb coder, lol :p
237 Followers
1 Contributions
21.1K
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