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Building Recommender Systems with Machine Learning and AI unleashes Frank Kane’s 9 years of experience building recommendation engines at Amazon, and everything he’s learned since then. You’ll apply collaborative filtering, matrix factorization, deep learning, and many other algorithms to the challenge of automatically recommending the perfect products, videos, or content to millions of individuals all the time. Featuring lots of hands-on activities, and real-world practical tips.
Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.
Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease.
Learn the tips and tricks behind Frank’s journey beyond 300,000 students and a million dollars on the Udemy online learning platform!
We’ll cover how to choose the topic most likely to succeed, audio and video production, marketing tips, and how to reach a large student audience. Change the world – and your life – by sharing your knowledge! This book shows you how.