Explore the fascinating intersection of mathematics and technology with this two-course set that brings together Introduction to Machine Learning and Mathematical Decision Making: Predictive Models and Optimization. First, learn how everything from search engines to navigation systems to game-playing robots got that way in 25 lessons taught by a pioneer researcher in machine learning. Then, discover the endless ways in which applying quantitative methods helps us problem solve and make smarter decisions in business, research, government, and other fields.
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Despite growing interest in the mathematical analysis of algorithms, basic information on methods and models has rarely been directly accessible to practitioners, researchers, or students. This book organizes and presents that knowledge, fully introducing today's primary techniques for mathematically analyzing algorithms.
This book introduces the mathematics that supports advanced computer programming and the analysis of algorithms. The primary aim of its well-known authors is to provide a solid and relevant base of mathematical skills - the skills needed to solve complex problems, to evaluate horrendous sums, and to discover subtle patterns in data.
A hands-on, easy-to-comprehend guide that is perfect for anyone who needs to understand algorithms. With the explosive growth in the amount of data and the diversity of computing applications, efficient algorithms are needed now more than ever. Programming languages come and go, but the core of programming--algorithms and data structures--remains the same. Absolute Beginner's Guide to Algorithms is the fastest way to learn algorithms and data structures.
Build State of the Art Machine Learning Models without a single line of code
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