Linear Algebraic Tools in Machine Learning and Data Science

Check out Krishnendu Chaudhury's book 📖 Math and Architectures of Deep Learning | http://mng.bz/K2ag 📖 For 40% off this book use the ⭐ DISCOUNT CODE: twitchaud40 ⭐ Learn the most important tools in the repertoire of a data scientist and machine learning practitioner – Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and Latent Semantic Analysis (LSA) – with the help of Krishnendu Chaudhury, a deep learning and computer vision expert with decade-long stints at both Google and Adobe Systems. 📚📚📚
Math and Architectures of Deep Learning | http://mng.bz/K2ag
For 40% off this book use discount code: twitchaud40
📚📚📚 About the book:
Math and Architectures of Deep Learning sets out the foundations of DL in a way that’s both useful and accessible to working practitioners. Each chapter explores a new fundamental DL concept or architectural pattern, explaining the underpinning mathematics and demonstrating how they work in practice with well-annotated Python code. You’ll start with a primer of basic algebra, calculus, and statistics, working your way up to state-of-the-art DL paradigms taken from the latest research. https://www.youtube.com/watch?v=n0RLz0rJ8gI