Fundamental Mathematical Concepts For Machine Learning in Science

Mathematics for Machine Learning. Learn about the prerequisite mathematics for applications in data science and machine learning.

A master class to learn convex optimization for ML and its applications to different fields and areas of engineering

Data Science Projects with Linear Regression, Logistic Regression, Random Forest, SVM, KNN, KMeans, XGBoost, PCA etc

This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms. In spite of the intensive research and development in this area, there does not exist a systematic treatment to introduce the fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized algorithms, nonconvex optimization, distributed and online learning, and projection free methods.

Learn Machine Learning, Statistics and Data Science Using R Programming from Scratch to Advanced with Real Life Projects