{ "item_title" : "Mathematical Foundations for Data Science and Optimization", "item_author" : [" Ahmet Goncu "], "item_description" : "The math that actually powers machine learning - explained once, correctly, and paired with code you can run.Most students learn linear algebra, calculus, probability, and optimization as four separate, disconnected courses - then struggle to see how any of it actually shows up in a gradient descent update, a covariance matrix, or a neural network's backward pass. Mathematical Foundations for Data Science and Optimization closes that gap: a single, rigorously written volume that builds the mathematics from first principles and shows, at every step, exactly how it translates into working Python.This book covers: Linear Algebra - systems of equations, matrix operations, vector spaces, eigenvalues and eigenvectors, and the decompositions (LU, QR, Cholesky, SVD) that make modern computation possible, culminating in a full derivation of Principal Component Analysis.Calculus - derivatives, partial derivatives, gradients, Jacobians, and Hessians, chain rule and Taylor expansion, built specifically toward the multivariable optimization that machine learning depends on.Probability - axioms, conditional probability and Bayes' theorem, random variables, expectation, and the distributions that matter in practice, including the Normal and Student's t-distributions with real simulated data and fitted density plots.Nonlinear Optimization - gradient descent, Newton's method, and stochastic gradient descent, with convergence theory made concrete through worked examples and real generated figures, not just abstract bounds.What sets this book apart: Every theorem is followed by a fully worked, step-by-step example - no results are left unillustratedEvery chapter includes runnable Python code (NumPy, SciPy, scikit-learn, Matplotlib)Whether you're a student preparing for a machine learning course, a self-taught engineer filling gaps in your mathematical foundation, or an instructor looking for a single reference that unifies these four subjects, this book is designed to be worked through, not just read - a desk reference you'll return to long after the first pass.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/819/198/9798191985336_b.jpg", "price_data" : { "retail_price" : "12.99", "online_price" : "12.99", "our_price" : "12.99", "club_price" : "12.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

Overview

Customers Also Bought

Details