Python machine learning

Explore the multidisciplinary nature of complex networks through machine learning techniquesStatistical and Machine Learning Approaches for Network Analysis provides an accessible framework for struct

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This

This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including re

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in r

The sixteen papers presented by Zhang (California State U.) and Tsai (U. of Illinois at Chicago) describe recent advances in machine learning applications in software engineering. They are organized i

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting

This book brings together - in an informal and tutorial fashion - the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic al

This volume constitutes the proceedings of the First Asian Conference on Machine Learning, ACML 2009, held in Nanjing, China, in November 2009.The 27 revised selected papers presented together with 3

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group.You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning models

Python is today's fastest growing programming language. This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

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