deep learning a practitioners approach

Download Book Deep Learning A Practitioners Approach in PDF format. You can Read Online Deep Learning A Practitioners Approach here in PDF, EPUB, Mobi or Docx formats.

Fundamentals Of Deep Learning

Author : Nikhil Buduma
ISBN : 1491925612
Genre :
File Size : 36. 99 MB
Format : PDF, ePub, Mobi
Download : 540
Read : 1023

Download Now

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.

Automatic Speech Recognition

Author : Dong Yu
ISBN : 9781447157793
Genre : Technology & Engineering
File Size : 24. 8 MB
Format : PDF, ePub, Docs
Download : 481
Read : 157

Download Now

This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.

Deep Learning

Author : Li Deng
ISBN : 1601988141
Genre : Computers
File Size : 49. 19 MB
Format : PDF, ePub
Download : 213
Read : 621

Download Now

Deep learning, Machine learning, Artificial intelligence, Neural networks, Deep neural networks, Deep stacking networks, Autoencoders, Supervised learning, Unsupervised learning, Hybrid deep networks, Object recognition, Computer vision, Natural language processing, Language models, Multi-task learning, Multi-modal processing

Machine Learning

Author : Kevin P. Murphy
ISBN : 9780262018029
Genre : Computers
File Size : 30. 9 MB
Format : PDF, Kindle
Download : 416
Read : 656

Download Now

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Deep Learning

Author : Stellan Ohlsson
ISBN : 9781139496759
Genre : Psychology
File Size : 52. 85 MB
Format : PDF, Mobi
Download : 698
Read : 553

Download Now

Although the ability to retain, process, and project prior experience onto future situations is indispensable, the human mind also possesses the ability to override experience and adapt to changing circumstances. Cognitive scientist Stellan Ohlsson analyzes three types of deep, non-monotonic cognitive change: creative insight, adaptation of cognitive skills by learning from errors, and conversion from one belief to another, incompatible belief. For each topic, Ohlsson summarizes past research, re-formulates the relevant research questions, and proposes information-processing mechanisms that answer those questions. The three theories are based on the principles of redistribution of activation, specialization of practical knowledge, and re-subsumption of declarative information. Ohlsson develops the implications of those mechanisms by scaling their effects with respect to time, complexity, and social interaction. The book ends with a unified theory of non-monotonic cognitive change that captures the abstract properties that the three types of change share.

Machine Learning Models And Algorithms For Big Data Classification

Author : Shan Suthaharan
ISBN : 9781489976413
Genre : Business & Economics
File Size : 73. 72 MB
Format : PDF
Download : 837
Read : 274

Download Now

This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random forest (an ensemble hierarchical approach), and deep learning (a layered approach) are highly suitable for the system that can handle such problems. This book helps readers, especially students and newcomers to the field of big data and machine learning, to gain a quick understanding of the techniques and technologies; therefore, the theory, examples, and programs (Matlab and R) presented in this book have been simplified, hardcoded, repeated, or spaced for improvements. They provide vehicles to test and understand the complicated concepts of various topics in the field. It is expected that the readers adopt these programs to experiment with the examples, and then modify or write their own programs toward advancing their knowledge for solving more complex and challenging problems. The presentation format of this book focuses on simplicity, readability, and dependability so that both undergraduate and graduate students as well as new researchers, developers, and practitioners in this field can easily trust and grasp the concepts, and learn them effectively. It has been written to reduce the mathematical complexity and help the vast majority of readers to understand the topics and get interested in the field. This book consists of four parts, with the total of 14 chapters. The first part mainly focuses on the topics that are needed to help analyze and understand data and big data. The second part covers the topics that can explain the systems required for processing big data. The third part presents the topics required to understand and select machine learning techniques to classify big data. Finally, the fourth part concentrates on the topics that explain the scaling-up machine learning, an important solution for modern big data problems.

Introduction To Machine Learning With Python

Author : Sarah Guido
ISBN : 1449369413
Genre : Computers
File Size : 40. 63 MB
Format : PDF, Docs
Download : 427
Read : 754

Download Now

Many Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data. Machine Learning with Python teaches you the basics of machine learning and provides a thorough hands-on understanding of the subject. You’ll learn important machine learning concepts and algorithms, when to use them, and how to use them. The book will cover a machine learning workflow: data preprocessing and working with data, training algorithms, evaluating results, and implementing those algorithms into a production-level system.

Top Download:

Best Books