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You want to learn Machine Learning and Deep Learning with Python, Scikit-Learn, Tenserflow and you don't know how to start? You don't need a big boring and expensive textbook. This book is the best one for everyone. Order your book Now!! Why this book is the best one for data scientist? Here are the reasons:The author has explored everything about machine learning and deep learning right from the basics. A simple language has been used. Many examples have been given, both theoretically and programmatically. Screenshots showing program outputs have been added. The book is written chronologically, in a step-by-step manner. Book Objectives: The Aims and Objectives of the Book: To help you understand the basics of machine learning and deep learning. Understand the various categoriesof machine learning algorithms. To help you understand how different machine learning algorithms work. You will learn how to implement various machine learning algorithms programmatically in Python. To help you learn how to use Scikit-Learn and TensorFlow Libraries in Python. To help you know how to analyze data programmatically to extract patterns, trends, and relationships between variables. Who this Book is for? Here are the target readers for this book: Anybody who is a complete beginner to machine learning in Python. Anybody who needs to advance their programming skills in Python for machine learning programming and deep learning. Professionals in data science. Professors, lecturers or tutors who are looking to find better ways to explain machine learning to their students in the simplest and easiest way. Students and academicians, especially those focusing on neural networks, machine learning, and deep learning. What do you need for this Book? You are required to have installed the foll
This book aims to demystify machine learning and deep learning for beginners using Python. It breaks down complex concepts into simple language, offering both theoretical explanations and practical, programmatic examples with screenshots of outputs. The content is structured chronologically, guiding readers from the foundational basics of ML and DL to implementing algorithms with Scikit-Learn and TensorFlow, and finally to analyzing data for patterns and relationships.
The book is positioned as an accessible entry point for individuals new to machine learning in Python, aiming to advance their programming skills in this domain. It is designed to be a practical resource for data science professionals, educators seeking simpler explanations for students, and academics focusing on neural networks and machine learning. The approach emphasizes clear language and step-by-step instruction, making it suitable for a broad audience interested in understanding and applying ML and DL concepts.
Page Count:
146
Publication Date:
2019-01-04
Publisher:
Amazon Digital Services LLC - KDP Print US
ISBN-10:
1793175853
ISBN-13:
9781793175854
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