Machine Learning Concepts with Python and the Jupyter Notebook Environment

Machine Learning Concepts with Python and the Jupyter Notebook Environment
PDF, ePUB
  • eBook:
    Machine Learning Concepts with Python and the Jupyter Notebook Environment: Using Tensorflow 2.0
  • Author:
    Nikita Silaparasetty
  • Edition:
    1 edition
  • Categories:
  • Data:
    October 6, 2020
  • ISBN:
    1484259661
  • ISBN-13:
    9781484259665
  • Language:
    English
  • Pages:
    317 pages
  • Format:
    PDF, ePUB

Book 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. 

Content

Part I: Artificial Intelligence, Machine Learning, and Deep Learning
Chapter 1: An Overview of Artificial Intelligence
Chapter 2: An Overview of Machine Learning
Chapter 3: Introduction to Deep Learning
Chapter 4: Machine Learning vs. Deep Learning
Chapter 5: Machine Learning With Python

Part II: The Jupyter Notebook
Chapter 6: Introduction to Jupyter Notebook
Chapter 7: Python Programming in Jupyter Notebook

Part III: The TensorFlow Library
Chapter 8: The Tensorflow Machine Learning Library
Chapter 9: Programming with Tensorflow
Chapter 10: Introducing Tensorflow 2.0
Chapter 11: Machine Learning Programming with Tensorflow 2.0

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