AWS Machine Learning Heroes are experts and thought leaders proficient with deep learning frameworks and are passionate enthusiasts of emerging Amazon ML technologies. Globally, there are around 30 AWS Machine Learning Heroes at the moment making the world a better place one day at a time.

This machine learning book covers the essential concepts as well as step-by-step instructions that are designed to help you get a solid understanding of how to manage and secure ML workloads in the cloud. As you progress through the chapters, you'll discover how to use several container and serverless solutions when training and deploying TensorFlow and PyTorch deep learning models on AWS. You'll also delve into proven cost optimization techniques as well as data privacy and model privacy preservation strategies in detail as you explore best practices when using each AWS.

This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects.

This step-by-step guide begins by helping you design and build penetration testing labs that mimic modern cloud environments running on AWS, Azure, and Google Cloud Platform (GCP).

The Outstanding Advocacy Award is given to an individual who has demonstrated exceptional leadership, commitment, and dedication in promoting technology best practices and solutions within the AWS ASEAN community.

Presented and defended undergraduate thesis in the Kaspersky Student Conference International Cup against other winners from four preliminary rounds held in America, Europe, Asia-Pacific and MEA, and Russia and the CIS.

Presented and defended undergraduate thesis in the Kaspersky Student Conference Asia Pacific, Middle East and Africa Cup in Hong Kong. Competed against tertiary and post-graduate students from the Asia Pacific, Middle East and African regions.