Jorge Vasquez | Duration: 2h 40m | Video: H264 1280x720 | Audio: AAC 48 kHz 2ch | 432 MB | Language: English
In this course, you are going to learn the skills you need to build, train, and deploy machine learning models in Amazon SageMaker, including how to create REST APIs to integrate them into your applications for solving real-world problems.
A fully managed machine learning service is a great place to start if you want to quickly get machine learning into your applications. In this course, Build, Train, and Deploy Machine Learning Models with Amazon SageMaker, you will gain the ability to create machine learning models in Amazon SageMaker and to integrate them into your applications. First, you'll learn the basics and how to set up SageMaker. Next, you'll discover how to build, train, and deploy models applied to Image Classification for breast cancer detection and how to integrate them into a REST API. Finally, you will even discover how to manage security and scalability in Amazon SageMaker. When you're finished with this course, you will have a foundational understanding of Amazon SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

Instructors: Jorge Barrero
Project Files * 6 lectures * 1h 35m
Video: MP4 1920x1080 48 KHz | English

Video: MPEG4 Video (H264) 1920x1080 24fps 1457kbps | Audio: AAC 48000Hz stereo 177kbps
Genre: eLearning | Duration: 1hr+ | Language: English | File size: 1.24 GB
In this tutorial, I share my process to make ANIMATICS AND STORYBOARDS in BLENDER