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Python for Deep Learning — Build Neural Networks in Python

By: Meta Brains

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eText | 24 August 2022 | Edition Number 1

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Master Data Science, TensorFlow, Artificial Intelligence, and Neural Networks with this comprehensive deep learning course for absolute beginners

Key Features

Fundamentals course designed for both beginners and experts alike
Use different frameworks in Python to solve real-world problems using deep learning and AI
Make predictions using linear regression, polynomial regression, and multivariate regression

Book Description

Python is famed as one of the best programming languages for its flexibility. It works in almost all fields, from web development to developing financial applications. However, it's no secret that Python's best application is in deep learning and artificial intelligence (AI) tasks.

You'll start with an introduction to deep learning where you'll focus on the fundamentals of the deep learning theory and find out how to use deep learning in Python, before moving on to artificial neural networks (ANNs). You'll learn how to use different frameworks in Python to solve real-world problems using deep learning and artificial intelligence. Next, you'll discover how to make predictions using linear regression, polynomial regression, and multivariate regression, and build artificial neural networks with TensorFlow and Keras. The video also covers convolutional neural networks (CNNs) at length and goes through the different components such as convolution layer, pooling layer, and fully connected layer. Finally, you'll wrap up CNN implementation in Python.

By the end of this course, you'll be able to use the concepts of deep learning to build neural networks in Python like a professional.

What you will learn

Get to grips with the fundamentals of the deep learning theory
Discover how to use deep learning in Python
Find out how to use different frameworks in Python
Build artificial neural networks with TensorFlow and Keras
Explore the implementation of ANNs and CNNs in Python

Who this book is for

This course is for both programming beginners and professionals who want to expand on their knowledge of deep learning, or professional mathematicians looking to learn how to analyze data programmatically. Prerequisites include basic mathematical skills and Python coding experience.