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Learner Reviews & Feedback for Analyze Datasets and Train ML Models using AutoML by DeepLearning.AI

4.5
stars
23 ratings
2 reviews

About the Course

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. Practical data science is geared towards handling massive datasets that do not fit in your local hardware and could originate from multiple sources. One of the biggest benefits of developing and running data science projects in the cloud is the agility and elasticity that the cloud offers to scale up and out at a minimum cost. The Practical Data Science Specialization helps you develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker. This Specialization is designed for data-focused developers, scientists, and analysts familiar with the Python and SQL programming languages and want to learn how to build, train, and deploy scalable, end-to-end ML pipelines - both automated and human-in-the-loop - in the AWS cloud....
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1 - 3 of 3 Reviews for Analyze Datasets and Train ML Models using AutoML

By Niyazi S

Jun 10, 2021

H​aving working experience with Sagemaker is valuable course setting is nice and material is up to date I was looking for getting some hands on experience working with the python and notebook. Also I gained some experience with Blazingtext algorithm and read about the material provided.

By Magnus M

Jun 11, 2021

The videos and links were good. The labs were a bit too easy, mostly about copying variable names from the previous section.

By Nabiul H K

Jun 8, 2021

Should have been more challenging