In this TensorFlow Deep Learning course, you will gain the skills and knowledge required to leverage TensorFlow to solve real-world Deep Learning problems. You will learn how to:
- Understand tensors and their variables
- Use TensorFlow's sequential and functional API
TensorFlow Deep Learning Training Delivery Methods
TensorFlow Deep Learning Training Benefits
Leverage artificial neural networks
Understand the strengths and limitations of TensorFlow
Use TensorFlow 2.x, from fundamentals to building blocksTrain, test, and evaluate a TensorFlow Model
Deploy a trained TensorFlow Model
Continue learning and face new challenges with after-course one-on-one instructor coaching
TensorFlow Deep Learning Training Outline
In this module, you will learn:
- The basics of artificial neural networks
- The lifecycle of building a TensorFlow model
- The basics of Deep Learning
- Layered architecture of TensorFlow
- Constants, variables and Tensors
Lab:
- Introduction to Tensors and Variables
In this module, you will learn how to:
- Use tf.data
- Define a Keras Model
- Build wide and deep models
Lab:
- Exploring tf.data
- Using TensorFlow sequential API
- Using TensorFlow functional API
In this module, you will learn about:
- Defining gradient descent
- Activation functions
- Hyperparameters
- Regularisation
Lab:
In this module, you will learn about:
- Basics of Feature Engineering
- Raw Data and Features
- Feature Crosses
- Transform
Lab:
- Feature Engineering
- Basic Feature Engineering in Keras
- Advanced Feature Engineering in Keras
- Exploring Tf.transform
In this module, you will learn about:
- Monitoring with TensorBoard
- Saving and Versioning Model
- Deploying Models
Lab:
- Using TensorBoard to Monitor the performance
