Welcome to the advanced machine learning on Google Cloud specialization.

In this specialization, you will learn how to apply machine learning at scale and how to build specialized machine learning models for images, sequences, and recommendations.

The first course is on building production machine learning systems.

We look at what to consider when building production machine learning models and provide an overview of static training, dynamic training, static inference, dynamic inference, and distributed training using TensorFlow 2.0 which uses the Keras API.

The second course is all about building image models.

You will learn about convolutional neural networks and build image classification models of various types.

The third course is on building sequence models.

Sequence models are used to address a variety of applications, including:

• financial time series prediction,

• speech recognition,

• music generation,

• sentiment classification,

• and machine translation.

We will focus on models used in natural language problems like text classification and translation.

Finally, we end this specialization with building real-world recommendation systems.

This brings together all the concepts that were covered in both the previous specialization and in this one.