• ISBN13: 9781484259665
• Binding: Paperback
• Subject: Computer Science and Information Technology
• Publisher: Springer Verlag
• Publisher Imprint: Springer
• Publication Date: January 1, 2020
• Pages: 290
• Original Price: EUR 64.99
• Language: English
• Edition: N/A
• Item Weight: 450 grams
• BISAC Subject(s): Artificial Intelligence / General

From the Back Cover
​Understand the fundamental concepts of machine learning with Python and TensorFlow 2.0, within the Jupyter Notebook environment. Even if you're an absolute beginner, develop a strong understanding of the crucial ideas without feeling intimidated by the immensity of the sector.
Start with a gentle introduction to artificial intelligence and machine learning to understand how the field has grown over the years and why it is still relevant. Then learn how the notebook interface has become increasingly popular for writing code--with Jupyter Notebook being preferred to a regular text editor or IDE.
Once these topics have been covered, you'll dive into the TensorFlow 2.0 library. Obtain a good understanding of what TensorFlow is, and how it has improved from its initial release. You'll be able to compare the two versions in a theoretical as well as practical way, and you'll go through the procedure required to convert code from TensorFlow 1.0 to TensorFlow 2.0.
Finally, you will work through projects that use TensorFlow 2.0 with Python and the Jupyter Notebook to help build your own neural networks for deep learning. This will enable you to put everything that you have learned from the book into practice. Each project is given in a step-by-step format for better comprehension.

Nikita Silaparasetty is a Data Scientist and an AI/Deep Learning Enthusiast specializing in Statistics and Mathematics. She is presently the head of the Indian based 'AI For Women' initiative, which aims to empower women in the field of Artificial Intelligence. She has strong experience programming using Jupyter Notebooks and a deep enthusiasm for TensorFlow and the potentials of Machine Learning. Through the book, she hopes to help readers become better at Python Programming using Tensorflow 2.0 with the help of Jupyter Notebooks, which can benefit them immensely in their Machine Learning journey.