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Opiniones y comentarios de aprendices correspondientes a Machine Learning With Big Data por parte de Universidad de California en San Diego

4.6
estrellas
2,080 calificaciones
435 reseña

Acerca del 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...

Principales reseñas

PR

Jul 19, 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.

BK

Mar 06, 2020

This is starting course for Machine Learning. Very well explained and after finishing this course, one will get interest in continuing and exploring further in Machine Learning field.

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376 - 400 de 418 revisiones para Machine Learning With Big Data

por Hendrik B

Feb 21, 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

Jun 01, 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

Aug 02, 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 Sebastián C L

Jul 12, 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

Nov 16, 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

Feb 19, 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

Aug 28, 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

May 10, 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.

por Anil B

Jan 21, 2019

It would have been better if more case studies to work were given. I am surprised that there is no working case study given for regression analysis.

por Mohan R S

May 30, 2020

The descriptive topics were The Handson exercise could be more elaborative. Many of the commands are just written but not explained.

por Alberto T

Jun 14, 2017

many basic of machine learning but not so specific to big data, only hands-on with pyspark is big-data related

por HILLEL D

Jun 21, 2020

Topics covered are good.

Outdated.

Hands-on needs to be updated. Exisitng set of 5th week contains error

por JAIDER M F T

May 13, 2020

El curso es introductorio no ahonda en los temas, me hubiese gustado que hubiese mostrado mas temas.

por Miguel T

Aug 17, 2018

I miss some technical information about machine learning techniques such as neural networks.

por Luis A A C

May 15, 2020

Very basic in terms of statistical techniques but liked the use of big data tools

por Akash R

Jun 06, 2020

this is more about ml classes, very less practical, only theoretical........

por Juan S H C

May 03, 2020

The Cloudera must to be checked. Too many errors in the Hands-On exercices

por PRERNA S

Mar 15, 2018

It was a basic course for initial understanding about Machine learning.

por Giorgi B

Sep 13, 2020

Very basic, and if you know machine learning only good for using knime

por Francisco J H A

Dec 24, 2019

The last week in my point of view is not linked to machine learning.

por Atharva J

Sep 21, 2020

Low volume for lecture videos, System setup is long and tedious .

por Carlos A A C

Apr 25, 2020

We dont see how to use things like hadoop map reduce or clustering

por Rahul P

Aug 02, 2019

The Hands-On exercises were good. The theory part was too shallow.

por Kartik K

Nov 23, 2018

The course should cover more topics about Machine Learning.

por Ivan S

Mar 01, 2017

Very basic things... Any examples for regression.