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Analyze Datasets and Train ML Models using AutoML(으)로 돌아가기

deeplearning.ai의 Analyze Datasets and Train ML Models using AutoML 학습자 리뷰 및 피드백

4.5
별점
260개의 평가
63개의 리뷰

강좌 소개

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....

최상위 리뷰

YA

2021년 11월 8일

Seriously I never expected to learn so many new methods, I am fascinated with the resources and the teaching techniques. Delivering information and great programmatic explanation.

HK

2021년 7월 7일

Excellent introductory course for Aws sagemaker. Justifies the specialization title as it is indeed practical oriented. Labs are of good quality as well.

필터링 기준:

Analyze Datasets and Train ML Models using AutoML의 69개 리뷰 중 26~50

교육 기관: Sam B C

2022년 1월 19일

I cannot proceed with the lab. It says I have reached the total lab usage time

교육 기관: Akshay B

2022년 6월 24일

T​he instructions were clear, provides a concise and to the point discussion concerning the topics being taught.

T​he coursework is well thought out, however, I would suggest possible improvements with two issues:

1​. The captions with the video are often unreliable/inaccurate which becomes a problem since the accent of one of the instructors was a little hard to understand and requires several rewatches to understand.

2​. The estimated times for the programme do not account for note making which increases the time by a lot since the videos discuss several topics in quick succession and the videos need to be paused to write notes often increasing the time several fold compared to what is suggested.

교육 기관: Tenzin T

2021년 8월 22일

Great! Highly recommended for emerging data scientist who are looking to gain practical knowledge on AWS.

교육 기관: Yin Q

2021년 7월 1일

The course is well organized and the lab is easy to follow. Thanks for making this course available!

교육 기관: Dylan B

2022년 5월 9일

Excellent instruction, made automating complicated machine learning problems seem easy!

교육 기관: Juan M

2022년 2월 16일

Easy step-by-step guide for beginners. Practical and theoretical usefull references.

교육 기관: Pitabas M

2021년 7월 25일

Gives a very good and quick introduction to the different features available in AWS.

교육 기관: Zuzana N

2022년 4월 11일

Very clear explanations. The course is not very difficult, it went really smoothly.

교육 기관: Endris M A

2022년 3월 18일

Excellent, Thank you Coursera for giving me this wornderfull opportunity.

교육 기관: Shankar K V

2021년 11월 20일

Amazing course to learn about various data science concepts and AWS tools

교육 기관: Serjesh S

2022년 2월 13일

Great way to understand the various component of Sagemaker echosystem

교육 기관: Pratik K

2021년 10월 12일

G​ood overview of general Data Science concepts and AWS Sagemaker.

교육 기관: Marry C C

2021년 9월 9일

Great courser to learn advance machine learning pipelines in AWS!

교육 기관: karthik v

2021년 9월 24일

This course really helped me understand about AWS services

교육 기관: Janzaib M

2022년 4월 17일

Very Hands On Practical Information for the Industry

교육 기관: Hamza A

2022년 3월 17일

great course ! thank you to all the instructors

교육 기관: Alcebiades A B F

2021년 8월 7일

Good contents if you study de jupyter notebooks

교육 기관: Flavio F

2021년 10월 8일

A​mazing. Best course regarding aws sagemaker.

교육 기관: Brenno M N S

2022년 4월 6일

I learnt a lot with this incredible course.

교육 기관: Viplove J G

2021년 10월 13일

It is a good course but i want to unenroll!

교육 기관: Stephen K

2022년 4월 1일

Excellent presentations with good content!

교육 기관: Santiago B

2022년 2월 11일

Es una buena introduccion al mundo de ML

교육 기관: Himasha J

2021년 11월 5일

great content , learn new aws services

교육 기관: Gourav R

2021년 8월 4일

great course ,real practical knowledge

교육 기관: Jonathan P

2022년 6월 29일

I​ found this course very helpful.