TensorFlow is a popular and 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 2.0 to build predictors, classifiers, generative models, neural networks and so on.
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Introduction
- TensorFlow 2.0 vs previous versions -- What's new
Setting up Tensoflow 2.0
Overview of TensorFlow 2.0 Features and Architecture
How Neural Networks Work
Using TensorFlow 2.0 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
- Programming experience in Python.
- Experience with the Linux command line.
21 hours (usually 3 days including breaks)
