The Hundred-Page Language Models Book
Read it:
https://github.com/aburkov/theLMbook
Read it:
https://github.com/aburkov/theLMbook
#LLM #NLP #ML #AI #PYTHON #PYTORCH
https://t.me/DataScienceM
👍7
February 19
Generative AI for beginners by Microsoft
21 Lessons teaching everything you need to know to start building Generative AI applications
Enroll Free: https://github.com/microsoft/generative-ai-for-beginners
21 Lessons teaching everything you need to know to start building Generative AI applications
Enroll Free: https://github.com/microsoft/generative-ai-for-beginners
#GenerativeAI #LLM #GAN #PYTHON #PYTORCH #ML #DEEPLEARNING #RAG
https://t.me/CodeProgrammer
👍13❤4🔥2
February 19
Pen and Paper Exercises in MachineLearning
Free 211-page PDF: arxiv.org/abs/2206.13446
GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises
Free 211-page PDF: arxiv.org/abs/2206.13446
GitHub: https://github.com/michaelgutmann/ml-pen-and-paper-exercises
#DataScientist #AI #ML #DataScience #LLM #PYTHON #PYTORCH #DEEPLEARNING #GenerativeAI
https://t.me/CodeProgrammer
👍15❤5
March 2
March 3
course lecture on building Transformers from first principles:
https://www.dropbox.com/scl/fi/jhfgy8dnnvy5qq385tnms/lectureattentionneuralnetworks.pdf?rlkey=fddnkonsez76mf8bzider3hrv&dl=0
The #PyTorch notebooks also demonstrate how to implement #Transformers from scratch:
https://github.com/xbresson/CS52422025/tree/main/labslecture07
https://www.dropbox.com/scl/fi/jhfgy8dnnvy5qq385tnms/lectureattentionneuralnetworks.pdf?rlkey=fddnkonsez76mf8bzider3hrv&dl=0
The #PyTorch notebooks also demonstrate how to implement #Transformers from scratch:
https://github.com/xbresson/CS52422025/tree/main/labslecture07
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming #Keras
https://t.me/CodeProgrammer✅
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March 26
Master PyTorch Faster with These Free Resources!
Whether you're just getting started with PyTorch or looking to refresh your deep learning skills, these two resources are all you need:
1. PyTorch Cheatsheet
A concise reference guide packed with essential PyTorch commands and patterns. Perfect for quick look-ups during development.
Download:
https://www.dropbox.com/scl/fi/e4xngykrfoubiw3xnd6fz/PyTorch-Cheatsheet.pdf?rlkey=vgx38ckps7aie120imgozgq4g&e=2&st=hgs06d4t&dl=0
2. Learn PyTorch Deep Learning with Hands-On Code
A beginner-friendly PDF with practical examples to help you build and train deep learning models using PyTorch from scratch.
Download:
https://www.dropbox.com/scl/fi/lfo7r6fnd8wjm3gp0jteh/Learn-PyTorch-Deep-Learning-with-Hands-On-Code.pdf?rlkey=mg9cxg41yerouzp0rklm8hqa2&e=2&st=c7k7rgay&dl=0
Save them, share them, and start building smarter models today!
#PyTorch #DeepLearning #AIResources #MachineLearning #Python #Cheatsheet #HandsOnAI
⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
Whether you're just getting started with PyTorch or looking to refresh your deep learning skills, these two resources are all you need:
1. PyTorch Cheatsheet
A concise reference guide packed with essential PyTorch commands and patterns. Perfect for quick look-ups during development.
Download:
https://www.dropbox.com/scl/fi/e4xngykrfoubiw3xnd6fz/PyTorch-Cheatsheet.pdf?rlkey=vgx38ckps7aie120imgozgq4g&e=2&st=hgs06d4t&dl=0
2. Learn PyTorch Deep Learning with Hands-On Code
A beginner-friendly PDF with practical examples to help you build and train deep learning models using PyTorch from scratch.
Download:
https://www.dropbox.com/scl/fi/lfo7r6fnd8wjm3gp0jteh/Learn-PyTorch-Deep-Learning-with-Hands-On-Code.pdf?rlkey=mg9cxg41yerouzp0rklm8hqa2&e=2&st=c7k7rgay&dl=0
Save them, share them, and start building smarter models today!
#PyTorch #DeepLearning #AIResources #MachineLearning #Python #Cheatsheet #HandsOnAI
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April 17
Dive deep into the world of Transformers with this comprehensive PyTorch implementation guide. Whether you're a seasoned ML engineer or just starting out, this resource breaks down the complexities of the Transformer model, inspired by the groundbreaking paper "Attention Is All You Need".
https://www.k-a.in/pyt-transformer.html
This guide offers:
By following along, you'll gain a solid understanding of how Transformers work and how to implement them from scratch.
#MachineLearning #DeepLearning #PyTorch #Transformer #AI #NLP #AttentionIsAllYouNeed #Coding #DataScience #NeuralNetworks
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April 30
Full PyTorch Implementation of Transformer-XL
If you're looking to understand and experiment with Transformer-XL using PyTorch, this resource provides a clean and complete implementation. Transformer-XL is a powerful model that extends the Transformer architecture with recurrence, enabling learning dependencies beyond fixed-length segments.
The implementation is ideal for researchers, students, and developers aiming to dive deeper into advanced language modeling techniques.
Explore the code and start building:
https://www.k-a.in/pyt-transformerXL.html
#TransformerXL #PyTorch #DeepLearning #NLP #LanguageModeling #AI #MachineLearning #OpenSource #ResearchTools
https://t.me/CodeProgrammer
If you're looking to understand and experiment with Transformer-XL using PyTorch, this resource provides a clean and complete implementation. Transformer-XL is a powerful model that extends the Transformer architecture with recurrence, enabling learning dependencies beyond fixed-length segments.
The implementation is ideal for researchers, students, and developers aiming to dive deeper into advanced language modeling techniques.
Explore the code and start building:
https://www.k-a.in/pyt-transformerXL.html
#TransformerXL #PyTorch #DeepLearning #NLP #LanguageModeling #AI #MachineLearning #OpenSource #ResearchTools
https://t.me/CodeProgrammer
👍7
May 6
rnn.pdf
5.6 MB
🔍 Understanding Recurrent Neural Networks (RNNs) Cheat Sheet!
Recurrent Neural Networks are a powerful type of neural network designed to handle sequential data. They are widely used in applications like natural language processing, speech recognition, and time-series prediction. Here's a quick cheat sheet to get you started:
📘 Key Concepts:
Sequential Data: RNNs are designed to process sequences of data, making them ideal for tasks where order matters.
Hidden State: Maintains information from previous inputs, enabling memory across time steps.
Backpropagation Through Time (BPTT): The method used to train RNNs by unrolling the network through time.
🔧 Common Variants:
Long Short-Term Memory (LSTM): Addresses vanishing gradient problems with gates to manage information flow.
Gated Recurrent Unit (GRU): Similar to LSTMs but with a simpler architecture.
🚀 Applications:
Language Modeling: Predicting the next word in a sentence.
Sentiment Analysis: Understanding sentiments in text.
Time-Series Forecasting: Predicting future data points in a series.
🔗 Resources:
Dive deeper with tutorials on platforms like Coursera, edX, or YouTube.
Explore open-source libraries like TensorFlow or PyTorch for implementation.
Let's harness the power of RNNs to innovate and solve complex problems!💡
Recurrent Neural Networks are a powerful type of neural network designed to handle sequential data. They are widely used in applications like natural language processing, speech recognition, and time-series prediction. Here's a quick cheat sheet to get you started:
📘 Key Concepts:
Sequential Data: RNNs are designed to process sequences of data, making them ideal for tasks where order matters.
Hidden State: Maintains information from previous inputs, enabling memory across time steps.
Backpropagation Through Time (BPTT): The method used to train RNNs by unrolling the network through time.
🔧 Common Variants:
Long Short-Term Memory (LSTM): Addresses vanishing gradient problems with gates to manage information flow.
Gated Recurrent Unit (GRU): Similar to LSTMs but with a simpler architecture.
🚀 Applications:
Language Modeling: Predicting the next word in a sentence.
Sentiment Analysis: Understanding sentiments in text.
Time-Series Forecasting: Predicting future data points in a series.
🔗 Resources:
Dive deeper with tutorials on platforms like Coursera, edX, or YouTube.
Explore open-source libraries like TensorFlow or PyTorch for implementation.
Let's harness the power of RNNs to innovate and solve complex problems!
#RNN #RecurrentNeuralNetworks #DeepLearning #NLP #LSTM #GRU #TimeSeriesForecasting #MachineLearning #NeuralNetworks #AIApplications #SequenceModeling #MLCheatSheet #PyTorch #TensorFlow #DataScience
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June 16
What is torch.nn really?
This article explains it quite well.
📌 Read
✉️ Our Telegram channels: https://t.me/addlist/0f6vfFbEMdAwODBk
When I started working with PyTorch, my biggest question was: "What is torch.nn?".
This article explains it quite well.
📌 Read
#pytorch #AIEngineering #MachineLearning #DeepLearning #LLMs #RAG #MLOps #Python #GitHubProjects #AIForBeginners #ArtificialIntelligence #NeuralNetworks #OpenSourceAI #DataScienceCareers
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July 11