Analyze Datasets and Train ML Models using AutoML
- Offered byCoursera
Analyze Datasets and Train ML Models using AutoML at Coursera Overview
Duration | 14 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Explore Free Course  |
Credential | Certificate |
Analyze Datasets and Train ML Models using AutoML at Coursera Highlights
- Reset deadlines in accordance to your schedule.
- Earn a Certificate upon completion
- Start instantly and learn at your own schedule.
Analyze Datasets and Train ML Models using AutoML at Coursera Course details
- In the first course of the Practical Data Science Specialization, you will learn foundational concepts for exploratory data analysis (EDA), automated machine learning (AutoML), and text classification algorithms.
- You will then perform automated machine learning (AutoML) to automatically train, tune, and deploy the best text-classification algorithm for the given dataset using Amazon SageMaker Autopilot.
- Next, you will work with Amazon SageMaker BlazingText, a highly optimized and scalable implementation of the popular FastText algorithm, to train a text classifier with very little code.
Analyze Datasets and Train ML Models using AutoML at Coursera Curriculum
Week 1: Explore the Use Case and Analyze the Dataset
Specialization overview
Welcome
Practical Data Science
Use case and data set
Data ingestion and exploration
Data visualization
Week 1 summary
Additional reading material
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Week 1
Week 2: Data Bias and Feature Importance
Introduction
Statistical bias
Statistical bias causes
Measuring statistical bias
Detecting statistical bias
Detect statistical bias with Amazon SageMaker Clarify
Approaches to statistical bias detection
Feature importance: SHAP
Summary
Additional reading material
Week 2
Week 3: Use Automated Machine Learning to train a Text Classifier
Introduction
Automated Machine Learning (AutoML)
AutoML Workflow
Amazon SageMaker Autopilot
Running experiments with Amazon SageMaker Autopilot
Amazon SageMaker Autopilot: evaluating output
Amazon SageMaker Autopilot demo
Model hosting
Week 3 summary
Additional reading material
Week 3
Week 4: Built-in algorithms
Introduction
Built in algorithms
Use cases and algorithms
Text analysis
Train a text classifier
Deploy the text classifier
Week 4 summary
Additional reading material
Course 1 Optional References
Acknowledgements
Week 4
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