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Machine Learning Concepts with Python and the Jupyter Notebook Environment: Using Tensorflow 2.0
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 TensorFlowTackle basic machine learning obstaclesDevelop 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.
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 TensorFlowTackle basic machine learning obstaclesDevelop 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.
325 pages, Kindle Edition
Published September 21, 2020
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Displaying 1 of 1 review
May 6, 2022
Wouldn't it be nice if there was a good introduction to Machine Learning with Python, in the Jupyter Notebook environment? Because this book is not it, and apparently there is no other such book. This seems to be an attempt to adress the absolute beginner in AI, programming (Python or otherwise) and ML. Kudos for trying, but the book sometimes does not explain what should be explained, and at other times explains the obvious. If the focus is on computational notebooks we do not need the background of text editors and IDE:s and why a notebook is better on a superficial feature level. We do want to understand the intrinsic advantages, efficient workflows and best practices of working in Jupyter Notebook, of which there is nothing worthwhile here. That's when you start checking the author's background in the field and it seems the author has no significant track record whatsoever. Whereupon there is no reason to spend any time on the final, ML part of the book. DNF.
Displaying 1 of 1 review