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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
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2,227 calificaciones
469 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

JG
24 de oct. 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.

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426 - 450 de 451 revisiones para Machine Learning With Big Data

por PRERNA S

15 de mar. de 2018

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

por Giorgi B

13 de sep. de 2020

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

por Francisco J H A

24 de dic. de 2019

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

por Atharva J

21 de sep. de 2020

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

por Carlos A A C

25 de abr. de 2020

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

por Rahul P

2 de ago. de 2019

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

por Kartik K

23 de nov. de 2018

The course should cover more topics about Machine Learning.

por Ivan S

1 de mar. de 2017

Very basic things... Any examples for regression.

por J. A H P

29 de dic. de 2016

It's ok for an extremely high-level overiew

por Palash V S

26 de ene. de 2018

Not hard, a very beginner-level course.

por Artur L

27 de oct. de 2017

Nice knowledge refresher

por shraddha s

25 de ago. de 2020

nice course

por Tobias O F

31 de jul. de 2017

The parts including KNIME was not interesting or educational, it was just an big grind. I feel once you are on a level to use KNIME you know that it is better (and easier) to use other frameworks where you have more control, therefor missing customers the program is meant for.

Additionally the last hands-on felt rushed and just copy-paste to some extent (to being able to complete the tasks), even for me having a lot of jupyter and machine learning background.

por Csaba P O

4 de oct. de 2017

This course is more "the very basics of machine learning" illustrated with some examples. The lectures were clear and logical, but honestly, very basic. Unfortunately the big data handsons (the ones with pyspark) are not explained very thoroughly, often they just state that "do this or do that" instead of explaining what is going on. All in all, I have expected more big-data related topics and less introduction to machine learning.

por Nwogbo b C

12 de jun. de 2020

The course was thrilling with a lot of hands-on activities..but the downside was that there were errors especially in the second and last hands-on and those bugs are so annoying giving the fact that some of us are still new in the big data world and have no clue to solving such problems

por Anirudha A M

20 de ago. de 2020

It should have been made clear that good experience in Spark is required for this course. I struggled with most of the commands and had to watch, re-watch most Spark related videos, google meanings of commands etc. The course experience was not very pleasant. Nevertheless, thank you.

por Erik P

17 de oct. de 2017

The virtual machine in this course no longer is functioning. PySpark update seems to not play nice. I think the content also needs some updating for more modern machine learning techniques.. like using big data with deep learning systems like tensor flow or PyTorch.

por Manfred K

14 de jul. de 2017

I expected course with more in-depth and more difficult examples, I learned about a few new concepts, most methods were repetitions for me.

por Alfonso A G

3 de dic. de 2016

Machine learning is too simplified and spark part is not even explained, also very little relation of all course with Big Data.

por LEONARDO R

9 de jun. de 2020

Considero que está algo desactualizado el curso y las herramientas de aprendizaje. Tenía mayor expectativa

por Michal Š

18 de nov. de 2016

Almost a useless course - ML overview using KNIME which gives no insight whatsoever.

por Ruijia W

25 de nov. de 2017

Too basic

por Beatrice C

14 de dic. de 2016

The course content is very poorly explained. The quiz questions don't really test what was taught in the lectures, and the assignments are just copying and pasting things. I feel like I still have a very poor understanding of what was supposedly covered in the course. I cannot generalise or apply the 'learned' information or skills to other topics or researches because I didn't actually understand the core concepts or how to use the programs.

por William R

19 de nov. de 2016

This is another course in UCSD's "Big Data" introductory course. The material is not pertinent to a specialty on big data technologies. Further the course does not increase one's knowledge of Machine Learning in any way that justifies spending the time in the course.

por Kamalesh P

23 de oct. de 2019

Regression is least bothered, less hands on