Machine Learning with SageMaker
Год выпуска: June 2025
Производитель: Published by Pearson via O'Reilly Learning
Сайт производителя:
https://learning.oreilly.com/course/machine-learning-with/9780135479452/
Автор: Nick Garner
Продолжительность: 8h 52m
Тип раздаваемого материала: Видеоурок
Язык: Английский + субтитры
Описание:
Master Cloud-Based Machine Learning on AWS
This course will teach critical skills to design and deploy scalable ML solutions. The core skills covered are:
• Data Preparation: Ingest, transform, and clean data using SageMaker
• Pipeline Automation: Build and deploy end-to-end ML workflows
• Solution Management: Monitor, secure, and optimize AWS-based ML systems
It offers hands-on AWS training that is ideal for software developers, data scientists, ML engineers, and DevOps professionals, this course blends theory with practical projects to help you design production-ready ML architectures, automate CI/CD pipelines for efficient deployment, implement security best practices for cloud-based systems.
Содержание
Introduction
Module 1 - Data Preparation for Machine Learning
Lesson 1 - Data Ingestion and Storage Basics
Lesson 2 - Data Transformation and Feature Engineering with SageMaker
Lesson 3 - Preparing Data for Modeling
Module 2 - ML Model Development
Lesson 4 - Choosing and Training Models in SageMaker
Lesson 5 - Model Evaluation and Bias Detection
Module 3 - Deployment and Orchestration of ML Workflows
Lesson 6 - Deploying Models with SageMaker
Lesson 7 - Automating ML Workflows with SageMaker Pipelines
Module 4 - ML Solution Monitoring, Maintenance, and Security
Lesson 8 - Monitoring and Optimizing ML Solutions
Lesson 9 - Securing ML Models and Data in SageMaker
Summary
Файлы примеров: отсутствуют
Формат видео: MP4
Видео: AVC, 1280×720, 16:9, 30.000 fps, 3 000 kb/s (0.017 bit/pixel)
Аудио: AAC, 44.1 KHz, 2 channels, 128 kb/s, CBR
Доп. информация:
You can find additional resources here:
https://bitbucket.org/awsdevguru/awsmlassoc/src/main/
