Machine Learning Concepts with Python and the Jupyter Notebook Environment: Using Tensorflow 2.0

By Silaparasetty, Nikita
Machine Learning Concepts with Python and the...

Details

Authors: Silaparasetty, Nikita
Format: Paperback
GTIN13: 9781484259665
ISBN10: 1484259661
Page Count: 290
Dimensions: 6.14x0.67x9.21
Publisher: Apress
Jacket Notes:

Create, execute, modify, and share machine learning applications with Python in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebooks instead of a text editor or a regular IDE.

You'll start by learning fundamental concepts in Python necessary for working with machine learning application development. Then use Jupyter Notebooks to improve the way you program with Python. After grounding your skills in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book.

Those who are new to machine learning can start in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier.

You will:

  • Program machine learning models in Python
  • Tackle basic machine learning obstacles
  • Develop in the Jupyter Notebooks environment

Description

Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebook instead of a text editor or a regular IDE.

You'll start by learning how to use Jupyter Notebooks to improve the way you program with Python. After getting a good grounding in working with Python in Jupyter Notebooks, you'll dive into what TensorFlow is, how it helps machine learning enthusiasts, and how to tackle the challenges it presents. Along the way, sample programs created using Jupyter Notebooks allow you to apply concepts from earlier in the book.

Those who are new to machine learning can dive in with these easy programs and develop basic skills. A glossary at the end of the book provides common machine learning and Python keywords and definitions to make learning even easier.

What You Will Learn

  • Program in Python and TensorFlow
  • Tackle basic machine learning obstacles
  • Develop in the Jupyter Notebooks environment

Who This Book Is For

Ideal for Machine Learning and Deep Learning enthusiasts who are interested in programming with Python using Tensorflow 2.0 in the Jupyter Notebook Application. Some basic knowledge of Machine Learning concepts and Python Programming (using Python version 3) is helpful.

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