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Voltar para Aprendizado de máquina com Big Data

Comentários e feedback de alunos de Aprendizado de máquina com Big Data da instituição Universidade da Califórnia, San Diego

4.6
estrelas
2,392 classificações

Sobre o curso

Want to make sense of the volumes of data you have collected? Need to incorporate data-driven decisions into your process? This course provides an overview of machine learning techniques to explore, analyze, and leverage data. You will be introduced to tools and algorithms you can use to create machine learning models that learn from data, and to scale those models up to big data problems. At the end of the course, you will be able to: • Design an approach to leverage data using the steps in the machine learning process. • Apply machine learning techniques to explore and prepare data for modeling. • Identify the type of machine learning problem in order to apply the appropriate set of techniques. • Construct models that learn from data using widely available open source tools. • Analyze big data problems using scalable machine learning algorithms on Spark. Software Requirements: Cloudera VM, KNIME, Spark...

Melhores avaliações

JG

24 de out de 2020

Excellent course. It teaches the basics with a great method and with practical exercises, involving real data. The sctructure is clear and it covers a good amount of topics. Well done San Diego!

PR

18 de jul de 2018

Excellent course, I learned a lot about machine learning with big data, but most importantly I feel ready to take it into more complex level although I realized there is lots to learn.

Filtrar por:

426 — 450 de 488 Avaliações para o Aprendizado de máquina com Big Data

por 19E15A0509 M

10 de jul de 2020

goog cource

por siva R

23 de ago de 2019

Good one !!

por Carlos S d l C

2 de abr de 2019

Good course

por SAURAV P

7 de nov de 2016

insightful

por Isco22

20 de mai de 2018

Too Basic

por Rohit K S

13 de out de 2020

Nice!

por Fabián S Á M

30 de set de 2020

Good!

por Yash B

20 de mai de 2021

Good

por Hien B L

19 de jul de 2020

GOOD

por Bodempudi N

23 de mai de 2020

good

por SHREYAS J C

18 de mai de 2020

Nope

por SELMI A

14 de abr de 2020

good

por Saravanan

28 de mar de 2019

Good

por Praveen k N

5 de mai de 2017

good

por AMIT B (

13 de mai de 2021

.

por Agaraoli A

10 de fev de 2017

-

por Hendrik B

21 de fev de 2018

It's better than the other courses of this specialization, but still I wouldn't say that the course is particularly good. Also, the instructors don't appear to care for the learning progress of the learners. There is next to no help via forums, for example. What I think was good is that the instructor attempts to explain the algorithms of the machine learning methods visually and comprehensively.

What I think is a joke is the way the quizzes are organized. The questions almost never deviate from a 'change a number or copy the code' style. Like this, you do not really learn anything instead of copying code and changing something. The quizzes need some additional parts where it is important to apply what is learned to new contexts. ADditionally, the instructors need to put more focus on explaining what certain parts of the code do and why certain parts of the codes are improtant- Otherwise, this course won't be worth more than learning by doing alone.

por Riccardo P

1 de jun de 2018

Not so happy... it would be a little bit better if I attended this one before the ML course by Andrew NG...

Here, the topics are just introduced and poorly demonstrated using Knime and Spark.

Maybe, I had wrong expectations but, given the course title, you need to push more on Spark and leave the ML introduction to better courses like Andrew's one or a dedicated one.

Don't spare too much time with stuff like Course 2 and get some risks

por Francisco P J

2 de ago de 2017

Some parts of the course are quite interesting, in concrete, the introduction to the Knime tool (so useful and open source tool which I will try to take a deep look on it as the course only provide a slightly overview). Otherwise, i think that the content is not enough, i don´t feel that I have fully understand the core of Machine Learning and its difference with other BD applications.

por Sarwar A

13 de out de 2020

I would like to give a three-star rating because of the following reasons:

1.Very Few Exercises

2.No challenging exercise

3.Only discussed Decision tree classifier

4.There are other important machine learning algorithms.

5.Overall I don't like the design of this course. It could have been degined to prepare learners for the industrial job

por SEBASTIAN C L

12 de jul de 2020

Un curso introductorio a las técnicas de machine learning. Los ejercicios en Knime permiten entender el paso a paso de un proyecto de ML, mientras que los ejercicios en Python son prácticamente replicar el código ofrecido y no agrega valor a menos que conozcas muy bien este lenguaje de programación

por Beate S

16 de nov de 2017

I liked the theory parts, but had a to of problems with the hands on exercises: I spent a tremendous amount of time on installing/trying to install the necessary software. And not everything worked properly on my Mac Laptop.

por Javier P C

19 de fev de 2020

I like this course, but is very old and doesn't have methods for programming like python or other. Please check the content and upgrade the software, for me, it doesn't work Cloudera VM and is very sad. More Quality.

por Joren Z

28 de ago de 2017

A bird's-eye-overview introduction of the field. It teaches you some terms and it gives you ideas about which fields might be interesting for you if you want to really learn how to do machine learning with big data.

por Victor J O O

9 de mai de 2020

The course start excellent talking about categorical predictions but I would like see a similar explanation for regression or numeric predictions. However, the course offer an excellent quality.