Introduction to Machine Learning and Deep Learning

Introduction to Machine Learning and Deep LearningIntroduction to Machine Learning and Deep LearningIntroduction to Machine Learning and Deep Learning

Introduction to Machine Learning and Deep Learning

Introduction to Machine Learning and Deep LearningIntroduction to Machine Learning and Deep LearningIntroduction to Machine Learning and Deep Learning
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Introduction to Machine Learning and Deep Learning: A Hands-On Starter's Guide

Samuel Dodge and Lina Karam

Copyright 2017-2020 Samuel Dodge and Lina Karam

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Conditions for Use and Distribution

 

Conditions of Use and Distribution for "Introduction to Machine Learning and Deep Learning: A Hands-On Starter's Guide," Samuel Dodge and Lina Karam follow below:

1. Authorship and copyright should be as follows:

Samuel Dodge and Lina Karam 

Copyright 2017-2023 Samuel Dodge and Lina Karam

2. Any redistribution and use of the content with or without modification including but not limited to derivatives of the work and code, must retain the above authorship and copyright note and should cite the following:

Samuel Dodge and Lina Karam, Introduction to Machine Learning and Deep Learning: A Hands-On Starter's Guide, Copyright 2017-2019 Samuel Dodge and Lina Karam. Available online at deeplearningtextbook.org 

Citing this book in Latex: 

@book{DodgeAndKaram-2019,

     title={Introduction to Machine Learning and Deep Learning: A Hands-On Starter's Guide},                             

     author = {Samuel Dodge and Lina Karam},

    publisher ={},

     note = {first version published 2017 and revised 2019. Available online at \url{https://www.deeplearningtextbook.org}},

     year = {2017-2019}

}

3. For educational use only and derivative work cannot be republished and/or resold



A Hands-On Starter's Guide: Table of Content

Introduction to Machine Learning and Deep Learning: A Hands-On Starter's Guide

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Title Page and Table of Content

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1. Python Basics, Unit Testing, and Introduction to Image Processing with Python

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2. Machine Learning Basics

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3. A Neural Network from Scratch and Application to Image Classification

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4. A Convolutional Neural Network from Scratch and Application to Image Classification

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5. Transfer Learning and Computer Vision in PyTorch

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6. Natural Language Processing with Recurrent Neural Networks in PyTorch and Tensorflow

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7. Bibliography

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Introduction to Deep Learning and Machine Learning

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