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AI Engineer

AI Deep Explorer | f... • 6m

The ultimate AI/ML roadmap for beginners 👇 𝗠𝗮𝘁𝗵𝘀 What to learn: • Linear Algebra • Calculus • Statistics Resources: • Practical Statistics for Data Science( https://amzn.to/446czl5 ) • Mathematics for Machine Learning( https://amzn.to/441selL ) • Essence of Linear Algebra (3Blue1Brown) • Brilliant & Khan Academy 𝗣𝘆𝘁𝗵𝗼𝗻 What to learn: • Native data structures (dictionaries, lists, sets, and tuples) • For and while loops • If-else conditional statements • Functions and classes • Numpy, Pandas, Sci-Kit Learn Resources: • W3Schools Python Course (free) • Python for Everybody Specialization (Coursera) • Machine Learning with Python and Scikit-Learn - Full Course 𝗗𝗮𝘁𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝘀 𝗮𝗻𝗱 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝘀 What to learn: • Arrays & Linked Lists • Trees & Graphs • HashMaps, Queues & Stacks • Sorting & Searching Algorithms • Dynamic Programming Resources: • Neetcode.io • Leetcode • Hackerrank 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 What to learn: • Linear, logistic and polynomial regression • Decision trees, random forests and gradient-boosted trees • Support vector machines • K-means and K-nearest neighbour clustering • Feature engineering • Evaluation metrics • Regularisation, bias vs variance tradeoff and cross-validation Resources: • Machine Learning Specialisation by Andrew Ng • The Hundred-Page ML Book • Hands-On ML with Scikit-Learn, Keras, and TensorFlow ( https://amzn.to/4jCmP92) • The Elements of Statistical Learning ( https://amzn.to/44aTjTH ) 𝗔𝗜 𝗮𝗻𝗱 𝗱𝗲𝗲𝗽 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 What to learn: • Neural Networks • Convolutional and Recurrent Neural Networks • Transformers • RAG, Vector Databases, LLM Fine Tuning • Reinforcement Learning Resources: • Deep Learning Specialization by Andrew Ng • Introduction to LLMs by Andrej Karpathy • Neural Networks: Zero to Hero • Reinforcement Learning Course - Lectures by David Silver 𝗠𝗟𝗢𝗽𝘀 What to learn: • Cloud technologies like AWS, GCP or Azure • Docker and Kubernetes • How to write production code • Git, CircleCI, Bash/Zsh Resources: • Practical MLOps (https://amzn.to/4iDPgCY ) • Designing Machine Learning Systems ( https://amzn.to/4iwZ2q5 )

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Day 2/100 : free AI resources sharing topic of day : machine learning Books ✓Machine Learning For Absolute Beginners by Oliver Theobald https://mrce.in/ebooks/Machine%20Learning%20for%20Absolute%20Beginners.pdf ✓Hands-On Machine Learning with

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AI Resources for Beginners Courses: 1. Stanford CS229: Machine Learning Full Course taught by Andrew NG also you can try his website DeepLearning. Al - https://www.youtube.com/playlist?list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU 2. Convolutional Neur

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My Favorite AI & ML Books That Shaped My Learning Over the years, I’ve read tons of books in AI, ML, and LLMs — but these are the ones that stuck with me the most. Each book on this list taught me something new about building, scaling, and underst

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