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. With Amazon SageMaker Clarify and Amazon SageMaker Data Wrangler, you will analyze a dataset for statistical bias, transform the dataset into machine-readable features, and select the most important features to train a multi-class text classifier. 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.
This course is part of the Practical Data Science on the AWS Cloud Specialization
Offered By
Practical Data Science on the AWS Cloud SpecializationDeepLearning.AIAbout this Course
Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat you will learn
Prepare data, detect statistical data biases, and perform feature engineering at scale to train models with pre-built algorithms.
Skills you will gain
- Statistical Data Bias Detection
- Multi-class Classification with FastText and BlazingText
- Data ingestion
- Exploratory Data Analysis
- Automated Machine Learning (AutoML)
Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses
Could your company benefit from training employees on in-demand skills?
Try Coursera for Business
Offered by
Syllabus - What you will learn from this course
Week 1: Explore the Use Case and Analyze the Dataset
Week 2: Data Bias and Feature Importance
Week 3: Use Automated Machine Learning to train a Text Classifier
Week 4: Built-in algorithms
Reviews
- 5 stars69.16%
- 4 stars21.94%
- 3 stars5.83%
- 2 stars2.22%
- 1 star0.83%
TOP REVIEWS FROM ANALYZE DATASETS AND TRAIN ML MODELS USING AUTOML
Very nice course, nice presentations. The difficulty level could have been a bit higher but all in all is a good course to get hands-on experience using data science tools on AWS.
really good course, direct to the point with aws. I really recommend create a account and review yourself all learning.
Great Introduction to AWS Sagemaker. The labs help you in putting various sage maker features in practice and must do to learn the concepts from the classes.
As always, I am overwhelmed with the course structure. Simple to learn and had enough practice to get started with cloud services.
About the Practical Data Science on the AWS Cloud Specialization
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