Duration
21 hours (usually 3 days including breaks)
Requirements
- Programming experience in Python.
- Experience with the Linux command line.
Audience
- Developers
- Data Scientists
Overview
TensorFlow is a popular machine learning library developed by Google for deep learning, numeric computation, and large-scale machine learning. TensorFlow 2.0, released in Jan 2019, is the newest version of TensorFlow and includes improvements in eager execution, compatibility and API consistency.
This instructor-led, live training (online or onsite) is aimed at developers and data scientists who wish to use Tensorflow 2.x to build predictors, classifiers, generative models, neural networks and so on.
By the end of this training, participants will be able to:
- Install and configure TensorFlow 2.x.
- Understand the benefits of TensorFlow 2.x over previous versions.
- Build deep learning models.
- Implement an advanced image classifier.
- Deploy a deep learning model to the cloud, mobile and IoT devices.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
- To learn more about TensorFlow, please visit: https://www.tensorflow.org/
Course Outline
Introduction
- TensorFlow 2.x vs previous versions — What’s new
Setting up Tensoflow 2.x
Overview of TensorFlow 2.x Features and Architecture
How Neural Networks Work
Using TensorFlow 2.x to Create Deep Learning Models
Analyzing Data
Preprocessing Data
Building a Model
Implementing a State-of-the-Art Image Classifier
Training the Model
Training on a GPU vs a TPU
Evaluating the Model
Making Predictions
Evaluating the Predictions
Debugging the Model
Saving a Model
Deploying a Model to the Cloud
Deploying a Model to a Mobile Device
Deploying a Model to an Embedded System (IoT)
Integrating a Model with Different Languages
Troubleshooting
Summary and Conclusion