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You're reading from Machine Learning for Developers Uplift your regular applications with the power of statistics, analytics, and machine learning

Product type Paperback

Published in Oct 2017

Publisher Packt

ISBN-13 9781786469878

Length 270 pages

Edition 1st Edition

Languages

Python

Tools

Scikit-learn

Concepts

Machine Learning

Authors (2):

Md Mahmudul Hasan

Rodolfo Bonnin

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Table of Contents (10) Chapters

Preface

1. Introduction - Machine Learning and Statistical Science

2. The Learning Process FREE CHAPTER

3. Clustering

4. Linear and Logistic Regression

5. Neural Networks

6. Convolutional Neural Networks

7. Recurrent Neural Networks

8. Recent Models and Developments

9. Software Installation and Configuration

References

Refer to the following content:

McCulloch, Warren S., and Walter Pitts,. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics 5.4 (1943): 115-133. Kleene, Stephen Cole. Representation of events in nerve nets and finite automata. No. RAND-RM-704. RAND PROJECT AIR FORCE SANTA MONICA CA, 1951.
Farley, B. W. A. C., and W. Clark, Simulation of self-organizing systems by digital computer. Transactions of the IRE Professional Group on Information Theory 4.4 (1954): 76-84.
Rosenblatt, Frank, The perceptron: A probabilistic model for information storage and organization in the brain, Psychological review 65.6 (1958): 386.Rosenblatt, Frank. x.
Principles of Neurodynamics: perceptrons and the Theory of Brain Mechanisms. Spartan Books, Washington DC, 1961
Werbos, P.J. (1975), Beyond Regression: New Tools for Prediction and Analysis...

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Authors (2)

Hasan

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Bonnin

Rodolfo Bonnin is a systems engineer and Ph.D. student at Universidad Tecnolgica Nacional, Argentina. He has also pursued parallel programming and image understanding postgraduate courses at Universitt Stuttgart, Germany. He has been doing research on high-performance computing since 2005 and began studying and implementing convolutional neural networks in 2008, writing a CPU- and GPU-supporting neural network feedforward stage. More recently he's been working in the field of fraud pattern detection with Neural Networks and is currently working on signal classification using machine learning techniques. He is also the author of Building Machine Learning Projects with Tensorflow and Machine Learning for Developers by Packt Publishing.

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