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A guide that explains how programs transform from source code to executables. Deep dive into ELF format, linking processes, and binary optimization techniques. Perfect for systems programmers, C developers, and anyone interested in low-level programming concepts.
Introduction to PyTorch, covering tensor initialization, operations, indexing, and reshaping.
This includes short and minimalistic few sessions covering fundamentals of Python programing language for geospatial data analysis.
Programming with POSIX Threads: David R. Butenhof
Companion webpage to the book "Mathematics For Machine Learning"
Mathematics for Machine Learning and Data Science
Mathematics for Machine Learning and Data Science Specialization - Coursera - deeplearning.ai - solutions and notes
Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.
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