Overall Duration : 136 Hours
Content of This Course
Introduction 15:24
Course Introduction
About The Exam
About This Course
Data Collection 01:01:58
Introduction
Concepts
General Data Terminology
Machine Learning Data Terminology
AWS Data Stores
AWS Migration Tools
AWS Helper Tools
Exam Tips
Streaming Data Collection 01:11:47
Introduction
Concepts
Kinesis Data Streams
Kinesis Firehose
Kinesis Video Streams
Kinesis Data Analytics
Exam Tips
Data Preparation 01:50:54
Introduction
Concepts
Categorical Encoding
Text Feature Engineering
Numeric Feature Engineering
Other Feature Engineering
Handling Missing Values
Feature Selection
Helper Tools
Exam Tips
Data Analysis and Visualization 01:16:38
Introduction
Concepts
Relationships
Comparisons
Distributions
Compositions
Choosing A Visualization
Exam Tips
Data Analysis and Visualization Lab
Modeling 01:22:11
Introduction
Concepts
Data Preparation
SageMaker Modeling
SageMaker Training
Exam Tips
Algorithms 02:20:49
Introduction
OPTIONAL - Why do we call them "Algorithms"?
Concepts
Regression
Clustering
Classification
Image Analysis
Anomaly Detection
Text Analytics
Reinforcement Learning
Forecasting
Ensemble Learning
Evaluation and Optimization 01:15:24
Introduction
Concepts
Monitoring and Analyzing Training Jobs
Evaluating Model Accuracy
Model Tuning
Exam Tips
Implementation and Operations 01:37:56
Introduction
Concepts
AI Developer Services
Amazon SageMaker Deployments
Other ML Deployment Options
Security
Monitor and Evaluate
Exam Tips
Wrap-Up 00:47
No comments:
Post a Comment