Machine Learning Concepts with Python and the Jupyter Notebook Environment Book Free DownloadCreate, 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.
Machine Learning Concepts with Python and the Jupyter Notebook Environment Description
From the Back Cover
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
About the Author
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.