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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
2,241 calificaciones
473 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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326 - 350 de 455 revisiones para Machine Learning With Big Data

por Roman J

30 de nov. de 2016

Have to make sure that code provided are fine and without problem... also, better instructions on how to go about the tool needed to use. Remember, we are learning and the amount of tools in Big Data ecosystem is vast...

por John C

9 de dic. de 2018

Interesting material. Ran into several issues with the hands on that could have been avoided. Loved learning more about Neo4J. The section on Spark needed more time and additional descriptions.

por Jürgen B

31 de oct. de 2018

Reasonable overview. The VM environment is a major challenge for my hardware. Takes more time to make it work than it should. I am wondering if a cloud solution e.g. GCP would be better.

por Jamal A

10 de may. de 2017

Great overview about the machine learning in general. There are still lots not covered specially the Neural Network algorithms. Learning Spark MLlib was great advantage of this course.

por Tariq A

27 de dic. de 2019

The fact that the assignments are graded means that there’s incentive to work on them, solve problems, and ask questions. Traditional online courses don’t offer that incentive.

por Dushyant

7 de sep. de 2017

Hands n exercises and corresponding quizzes are great !Content could be more detailed, but may be I felt it so given my past exposure to ML. I enjoyed learning Knime and Spark.

por SUNITHA N

4 de dic. de 2017

The precise definitions for many commonly used terms were very helpful. You do not find these details in many books or documents. Also, using KNIME was also interesting

por Santiago Z

23 de ago. de 2020

Good course, but I found several problems in the virtual machine and it was difficult to solve them with the forum info. I had to rebuild the vm several times.

por Thomas H

27 de nov. de 2016

Good overview of working with SPARK and KNIME - acceptable little theoretical background for all the presented concepts for the sake of application use.

por vishal c

12 de sep. de 2017

This is a good course to understand how we can apply basic ML algorithm like classification, clustering using KNIME and Spark ML on very high level.

por Gustavo I M

3 de jul. de 2019

Good, would be better if was in portuguese. and sometime is very painful configure the machine. But is a good course, better than the previus 3

por MartinsT

12 de nov. de 2020

In my opinion this is one of the best courses in Big Data specialization. I hghly recommend it, because of the theory AND practical tasks.

por Ofer K

5 de oct. de 2020

I was expecting a deeper coverage of the ML algorithm, however the course was fun and it was useful for me to get acquainted with KNIME

por Miguel A R B

12 de ene. de 2020

There was a good explanation of concepts, but I think it was possible to include more themes or empathize more in other techniques.

por Matteo B

5 de abr. de 2018

This course gives a good overview of the main machine learning techniques to analyze data using either spark or a GUI tool (KNIME).

por Andres V N

8 de jun. de 2020

great course, felt it was a bit basic for some stuff, would've liked more hands on.

Liked working with 2 tools, KNIME and Pyspark

por Sun W

24 de sep. de 2019

Generally its good content. However the VM setup is still horrible. Many time wasted on debugging and set up environment.

por Jose R Z

3 de sep. de 2019

The concepts in the course are very good but very basics in machine learning, it's a good introduction to knime and spark

por Irfan S

25 de nov. de 2017

Good course for new comers. Regression and Clustering concepts were explained in very high level and need some in depth.

por Teresa S

30 de ene. de 2018

Very interesting course that will help us to understand how machine learning course works and also to analyze data.

por Stefan V

19 de ago. de 2020

Spark was too much for my machine to handle, but working with Knime was a nice visual and guided experience to ML.

por Silvia C R S

18 de nov. de 2017

Very practical and interesting course! Ideal for people who does not have previous knowledge in Machine Learning.

por Hugo d J M Y

12 de feb. de 2017

not enough work in the other machine learning models (the course centered the main part of it to classification )

por Raul

26 de ago. de 2018

105/5000

I lack to have more examples of a complete solution, applying all the concepts in a generic problem.

por Dev A S

19 de ene. de 2020

The instructor is explaining well. But still in some weeks there is a gap between the Hands on and theories