Deep Learning Fundamentals with Keras

Description

In this course, you will learn:

• You'll discover about intriguing deep learning applications and why learning how to harness deep learning capabilities is so rewarding.
• Neural networks will be discussed, as well as how they learn and update their weights and biases.
• The vanishing gradient problem will be discussed.
• You'll learn how to use the Keras library to create a regression model.
• You'll learn how to use the Keras library to create a classification model.
• You'll learn about supervised deep learning models like convolutional neural networks and recurrent neural networks, as well as how to use the Keras library to build a convolutional neural network.
• Unsupervised learning models such as autoencoders will be discussed.

Syllabus:

1. Introduction to Deep Learning

• Introduction to Deep Learning
• Biological Neural Networks
• Artificial Neural Networks - Forward Propagation

2. Artificial Neural Networks

• Gradient Descent
• Backpropagation
• Vanishing Gradient
• Activation Functions

3. Deep Learning Libraries

• Introduction to Deep Learning Libraries
• Regression Models with Keras
• Classification Models with Keras

4. Deep Learning Models

• Shallow and Deep Neural Networks
• Convolutional Neural Networks
• Recurrent Neural Networks
• Autoencoders

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