Deep Learning - Artificial Neural Networks with TensorFlow: Master Machine Learning and Neural Networks for Data Science

Lazy Programmer

€8.99 ~~€90.99~~

Video Feb 2023 4hrs 47mins 1st Edition

Lazy Programmer

€8.99 ~~€90.99~~

Video Feb 2023 4hrs 47mins 1st Edition

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Key benefits

Understand the utilization of TensorFlow 2 to construct artificial neural networks
The course covers the basics of machine learning, classification, and regression
Explore the connection between artificial neural networks and biological neural networks

Description

TensorFlow is the world’s most popular library for deep learning, and it is built by Google. It is the library of choice for many companies doing AI and machine learning. So, if you want to do deep learning, you got to know TensorFlow. In this course, you will learn how to use TensorFlow 2 to build deep neural networks. We will first start by learning the basics of machine learning, classification, and regression. Then in the next section, we will understand the connection between artificial neural networks and biological neural networks and how that inspires our thinking in the field of deep learning. In the last two sections, you will learn about loss functions to understand mean squared error, binary cross entropy, and categorical cross entropy and gradient descent to understand stochastic gradient descent, momentum, variable and adaptive learning rates, and Adam optimization. By the end of this course, we will have understood how to use TensorFlow for artificial neural networks in deep learning.

Who is this book for?

This course is designed for anyone interested in deep learning and machine learning, anyone who wants to implement deep neural networks in TensorFlow 2, or anyone interested in building a foundation for convolutional neural networks, recurrent neural networks, LSTMs (Long Short Term Memory), and transformers. One must have decent Python programming skills and should be comfortable with data science libraries such as NumPy and Matplotlib.