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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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Data Science Interview Questions 💡 Here is your curated list for Data Science interviews! ✨ Join Best TG Channels https://t.me/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 #DataScience #AI #MachineLearning #LLM #TechJobs #InterviewPrep
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🔖 The Big Book on Fine-Tuning LLMs A free 115-page book dedicated to the retraining of large language models. 📚 It's suitable for those who want to understand how to prepare datasets, configure training, and improve the quality of LLMs for their tasks. 🚀 #LLM #FineTuning #AI #MachineLearning #DataScience #Tech ✨ Join Best TG Channels https://t.me/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
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The only LLM cheat sheet you'll ever need 🚀 Covers the main concepts, architectures, and practical applications. ### Basics - Tokens (tokenization, BPE) - Embeddings (cosine similarity) - Attention mechanism (Attention formula, Multi-Head Attention) ### Transformer architecture and its variants - BERT (models with only an encoder) - GPT (models with only a decoder) - T5 (models with an encoder and a decoder) ### Large language models (LLMs) - Prompting (context length, Chain-of-Thought) - Pre-training (SFT, PEFT/LoRA) - Preference tuning (Reward Model, Reinforcement Learning) - Optimizations (Mixture of Experts, Distillation, Quantization) ### Applications - LLM-as-a-Judge (LaaJ) - RAG (Retrieval-Augmented Generation) - Agents (ReAct) - Reasoning models (Scaling) ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A #LLM #AI #MachineLearning #DeepLearning #PromptEngineering #Tech
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