Chevron Left
Volver a Analyze Datasets and Train ML Models using AutoML

Opiniones y comentarios de aprendices correspondientes a Analyze Datasets and Train ML Models using AutoML por parte de deeplearning.ai

4.5
estrellas
280 calificaciones

Acerca del Curso

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....

Principales reseñas

YA

8 de nov. de 2021

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

7 de jul. de 2021

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

Filtrar por:

1 - 25 de 74 revisiones para Analyze Datasets and Train ML Models using AutoML

por Nabiul H K

8 de jun. de 2021

por Etienne T

2 de ago. de 2021

por Michael S

29 de jul. de 2021

por Magnus M

11 de jun. de 2021

por Anmol D

2 de jul. de 2021

por Sebastián G

1 de oct. de 2021

por Niyazi S

10 de jun. de 2021

por Jens B

10 de jul. de 2021

por Anurag L

22 de jun. de 2021

por Deleted A

14 de jun. de 2021

por Parag K

22 de oct. de 2021

por Francisco M G S

9 de ago. de 2021

por Alireza M

10 de jul. de 2021

por Phillip B

30 de jun. de 2021

por Karunanidhi M

29 de jul. de 2021

por Olle G

25 de jun. de 2021

por Adrien C

21 de sep. de 2021

por Adam M

6 de oct. de 2021

por Mark P

13 de sep. de 2021

por Mattias L

19 de jul. de 2021

por Yousef A

9 de nov. de 2021

por alaa a

28 de jul. de 2021

por Hitesh K

8 de jul. de 2021

por yugesh v

26 de jul. de 2021

por Ramesh K L

9 de ago. de 2021