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.
本课程是 Practical Data Science on the AWS Cloud 专项课程 专项课程的一部分
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Practical Data Science on the AWS Cloud 专项课程deeplearning.ai课程信息
Working knowledge of ML & Python, familiarity with Jupyter notebook & stat, completion of the Deep Learning & AWS Cloud Technical Essentials courses
对员工进行热门技能培训能否为您的公司带来益处？
体验 Coursera 企业版您将学到的内容有
Prepare data, detect statistical data biases, and perform feature engineering at scale to train models with pre-built algorithms.
您将获得的技能
- 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
对员工进行热门技能培训能否为您的公司带来益处？
体验 Coursera 企业版
授课大纲 - 您将从这门课程中学到什么
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
审阅
- 5 stars69.62%
- 4 stars21.77%
- 3 stars5.73%
- 2 stars2%
- 1 star0.85%
来自ANALYZE DATASETS AND TRAIN ML MODELS USING AUTOML的热门评论
Very useful content and helpful labs. Labs sessons expired in 2 hours and no work could be saved which is frustrating, make sure to submit work ASAP before diving into the detailed content.
Great course! The only thing that's not specified is the cost of the tools we learn how to use. Is SageMaker free, or is there a cost?
really good course, direct to the point with aws. I really recommend create a account and review yourself all learning.
Overall great course. Presentation by the instructors was very well done. The labs were a bit too easy, though. Exercises usually only consisted of copying and pasting a missing value from A to B.
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