The ultimate AI/ML roadmap for beginners ๐ ๐ ๐ฎ๐๐ต๐ What to learn: โข Linear Algebra โข Calculus โข Statistics Resources: โข Practical Statistics for Data Science( https://amzn.to/446czl5 ) โข Mathematics for Machine Learning( https://amzn.to/441selL ) โข Essence of Linear Algebra (3Blue1Brown) โข Brilliant & Khan Academy ๐ฃ๐๐๐ต๐ผ๐ป What to learn: โข Native data structures (dictionaries, lists, sets, and tuples) โข For and while loops โข If-else conditional statements โข Functions and classes โข Numpy, Pandas, Sci-Kit Learn Resources: โข W3Schools Python Course (free) โข Python for Everybody Specialization (Coursera) โข Machine Learning with Python and Scikit-Learnโ-โFull Course ๐๐ฎ๐๐ฎ ๐๐๐ฟ๐๐ฐ๐๐๐ฟ๐ฒ๐ ๐ฎ๐ป๐ฑ ๐ฎ๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐ What to learn: โข Arrays & Linked Lists โข Trees & Graphs โข HashMaps, Queues & Stacks โข Sorting & Searching Algorithms โข Dynamic Programming Resources: โข Neetcode.io โข Leetcode โข Hackerrank ๐ ๐ฎ๐ฐ๐ต๐ถ๐ป๐ฒ ๐น๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด What to learn: โข Linear, logistic and polynomial regression โข Decision trees, random forests and gradient-boosted trees โข Support vector machines โข K-means and K-nearest neighbour clustering โข Feature engineering โข Evaluation metrics โข Regularisation, bias vs variance tradeoff and cross-validation Resources: โข Machine Learning Specialisation by Andrew Ng โข The Hundred-Page ML Book โข Hands-On ML with Scikit-Learn, Keras, and TensorFlow ( https://amzn.to/4jCmP92) โข The Elements of Statistical Learning ( https://amzn.to/44aTjTH ) ๐๐ ๐ฎ๐ป๐ฑ ๐ฑ๐ฒ๐ฒ๐ฝ ๐น๐ฒ๐ฎ๐ฟ๐ป๐ถ๐ป๐ด What to learn: โข Neural Networks โข Convolutional and Recurrent Neural Networks โข Transformers โข RAG, Vector Databases, LLM Fine Tuning โข Reinforcement Learning Resources: โข Deep Learning Specialization by Andrew Ng โข Introduction to LLMs by Andrej Karpathy โข Neural Networks: Zero to Hero โข Reinforcement Learning Courseโ-โLectures by David Silver ๐ ๐๐ข๐ฝ๐ What to learn: โข Cloud technologies like AWS, GCP or Azure โข Docker and Kubernetes โข How to write production code โข Git, CircleCI, Bash/Zsh Resources: โข Practical MLOps (https://amzn.to/4iDPgCY ) โข Designing Machine Learning Systems ( https://amzn.to/4iwZ2q5 )
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