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Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

Name: Machine Learning for Hackers: Case Studies and Algorithms to Get You Started
Price: 34.15 USD
Availability: InStock
Rating: 3.8 (61 reviews)

3.80 of 5 Stars: Security & Encryption - Machine Learning for Hackers: Case Studies and Algorithms to Get You Started

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Description

Book Synopsis: If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.

Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you’ll learn how to analyze sample datasets and write simple machine learning algorithms.

Machine Learning for Hackers is ideal for programmers from any background, including business, government, and academic research.

Develop a naïve Bayesian classifier to determine if an email is spam, based only on its text
Use linear regression to predict the number of page views for the top 1,000 websites
Learn optimization techniques by attempting to break a simple letter cipher
Compare and contrast U.S. Senators statistically, based on their voting records
Build a “whom to follow” recommendation system from Twitter data

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Looking to level up your programming skills and dive into the world of machine learning? Look no further! Machine Learning for Hackers is the perfect book to get you started. With its hands-on approach and focus on practical case studies, this book will show you how to use machine learning algorithms to automate tasks and crunch data. Whether you're a business professional, a government employee, or a researcher, this book is designed for programmers from all backgrounds.

If you're tired of theory-heavy textbooks that leave you scratching your head, Machine Learning for Hackers is the solution. Authors Drew Conway and John Myles White take a different approach, using the R programming language and real-world examples to teach you the ropes. You'll learn how to build a naïve Bayesian classifier to detect spam emails, predict website page views using linear regression, and even break simple ciphers using optimization techniques.

But it doesn't stop there. Machine Learning for Hackers goes beyond the basics and dives into more advanced topics, such as comparing and contrasting U.S. Senators based on their voting records, and building recommendation systems from Twitter data. With this book, you'll gain the knowledge and skills to tackle real-world problems and make data-driven decisions.

Don't miss out on this opportunity to become a machine learning expert. Get your hands on Machine Learning for Hackers and unlock the power of algorithms to automate tasks and uncover insights. Start your journey today!

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