Requirements
- A little Python programming experience wouldn’t hurt 😉
Description
In this course, you’ll learn how to use Google TensorFlow to build your own deep learning models. We’ll take you from the basics of artificial neural networks and later show you how to build them using Keras and TensorFlow. We’ll walk through practical examples so that you can get a hand-on experience at working with TensorFlow and Keras.Who this course is for:
- Individual who would like to learn about deep learning
What you’ll Learn
- Deep Learning using Keras and TensorFlow
- Artificial Neural Networks
- How Artificial Neural Networks Work
- How Artificial Neural Networks Learn
- Loss Functions used in Artificial Neural Networks
- Activation Functions used in Artificial Neural Networks
- Cost Functions used in Artificial Neural Networks
- Optimizer Functions used in Artificial Neural Networks
- What Backpropagation is
- Different Types of Gradient Descent
- How to Choose an Activation Function
- Preparing your Data for Deep Learning Models
- Monitoring Loss Functions
- Monitoring Model Metrics
- Use of CallBacks in Deep Learning
- Fighting overfitting in TensorFlow
- Convolutional Neural Networks
