Deep Learning with Keras and Tensorflow
Taking an approach that uses the latest developments in the Python ecosystem, you’ll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We’ll explore a variety of approaches to classificatio
Python Deep Learning Projects: 9 projects demystifying neural network and deep learning models for building intelligent systems By 作者: Matthew Lamons – Rahul Kumar – Abhishek Nagaraja ISBN-10 书号: 1788997093 ISBN-13 书号: 9781788997096 出版日期: 2018-10-31 pages 页数: (670) Deep learning has been gradually
1. 概述类 首先是概述类论文，先后有2013年的“Representation Learning: A Review and New Perspectives”和2015年的”Deep Learning in Neural Networks: An Overview”两篇。 上传了较新的一篇。 3. 分布式计算 分布式计算方面论文涉及到具体解决计算能力的问题。有2012年的两篇论文Building High-level Features Using Large Scale Unsupervised Learning和Large Scale Distributed Deep Networks，
eep Learning: Recurrent Neural Networks in Python: LSTM, GRU, and more RNN machine learning architectures in Python and Theano (Machine Learning in Python) by LazyProgrammer English | 8 Aug 2016 | ASIN: B01K31SQQA | 86 Pages | AZW3/MOBI/EPUB/PDF (conv) | 1.44 MB Like Markov models, Recurrent Neural
Deep Learning, Vol. 2: From Basics to Practice By 作者: Andrew Glassner Pub Date: 2018 ISBN: n/a Pages: (914 of 1750) Format: PDF Publication Date: February 19, 2018 Language: English ASIN: B079Y1M81K People are using the tools of deep learning to change how we think about science, art, engineering, b
Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along w
Deep learning simplified by taking supervised, unsupervised, and reinforcement learning to the next level using the Python ecosystem Key Features • Build deep learning models with transfer learning principles in Python • implement transfer learning to solve real-world research problems • Perform co
Mastering Machine Learning with R - Second Edition by Cory Lesmeister English | 24 Apr. 2017 | ASIN: B01N5XJ3O0 | 420 Pages | AZW3 | 4.42 MB Key Features Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST Understand the benefits and potential pitfall
Machine Learning Made Easy with R: An Intuitive Step by Step Blueprint for Beginners by N.D Lewis English | 7 May 2017 | ISBN: 1546483756 | 356 Pages | PDF | 8.39 MB Finally, A Blueprint for Machine Learning with R! Machine Learning Made Easy with R offers a practical tutorial that uses hands-on e
Master machine learning techniques with R to deliver insights for complex projects About This Book Get to grips with the application of Machine Learning methods using an extensive set of R packages Understand the benefits and potential pitfalls of using machine learning methods Implement the numero
About This Book Load, store, edit, and visualize data using OpenCV and Python Grasp the fundamental concepts of classification, regression, and clustering Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide Evaluate, compare, and choose the right algo
What is Machine Learning? What problems does it try to solve? What are the main categories and fundamental concepts of Machine Learning systems? • The main steps in a typical Machine Learning project. • Learning by fitting a model to data. • Optimizing a cost function. • Handling, cleaning, and prep
Chapter 1, A Taste of Machine Learning, will gently introduce you to the different subfields of machine learning, and explain how to install OpenCV and other essential tools in the Python Anaconda environment. Chapter 2, Working with Data in OpenCV and Python, will show you what a typical machine l
Machine Learning for OpenCV by Michael Beyeler English | 14 July 2017 | ISBN: 1783980281 | ASIN: B0713QL4T3 | 382 Pages | AZW3 | 7.03 MB Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide. About This Book Load, store, edit, and visualize
https://github.com/PacktPublishing/Practical-Machine-Learning-Cookbook.git Practical Machine Learning Cookbook by Atul Tripathi English | 14 Apr. 2017 | ASIN: B01JLBMC9K | 570 Pages | AZW3 | 38.79 MB Key Features Implement a wide range of algorithms and techniques for tackling complex data Improv
Feature Engineering for Machine Learning Principles and Techniques for Data Scientists Feature engineering is a crucial step in the machine-learning pipeline, yet this topic is rarely examined on its own. With this practical book, you’ll learn techniques for extracting and transforming features—the
Machine Learning Algorithms By 作者: Giuseppe Bonaccorso ISBN-10 书号: 1785889621 ISBN-13 书号: 9781785889622 Release 出版日期: 2017-08-04 pages 页数: (449) List Price: $49.99 Book Description Build strong foundation for entering the world of Machine Learning and data science with the help of this compre
Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances By 作者: Zsolt Nagy ISBN-10 书号: 1789801656 ISBN-13 书号: 9781789801651 出版日期: 2018-12-12 pages 页数: (330) Machine learning and neural networks are pillars on which you can build i
Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R by V Kishore Ayyadevara Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and s
该代码是http://blog.csdn.net/qq_29656961/article/details/78155792博客里面的代码，代码里面有要用到的图片资源和音乐资源。
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