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All you need to know about Machine Learning in a hundred pages. Supervised and unsupervised learning, support vector machines, neural networks, ensemble methods, gradient descent, cluster analysis and dimensionality reduction, autoencoders and transfer learning, feature engineering and hyperparameter tuning! Math, intuition, illustrations, all in just a hundred pages!
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**Brand Description: The Hundred-Page Machine Learning Book**
The Hundred-Page Machine Learning Book, authored by Andriy Burkov, is a transformative resource designed for aspiring machine learning professionals and enthusiasts. This concise guide distills complex concepts such as supervised and unsupervised learning, neural networks, and dimensionality reduction into just a hundred pages. It's an ideal starting point for software engineers, data scientists, and curious learners aiming to understand the fundamentals of machine learning and artificial intelligence.
The book features accessible explanations, intuitive illustrations, and practical insights drawn from Andriy's extensive experience in the field, including his work on natural language processing. Readers can explore various learning formats, from e-books to paperback, with the option to "pay what you want" for digital copies. Additionally, a companion wiki provides updated resources and further reading to enhance the learning experience. With industry endorsements from leaders at LinkedIn, Amazon, and eBay, this book is your gateway to mastering machine learning and unlocking new career opportunities in an evolving technological landscape.
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Science and Education
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