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Machine Learning With Big Data に戻る

カリフォルニア大学サンディエゴ校 による Machine Learning With Big Data の受講者のレビューおよびフィードバック

4.6
2,392件の評価

コースについて

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...

人気のレビュー

JG

2020年10月24日

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

2018年7月18日

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.

フィルター:

Machine Learning With Big Data: 376 - 400 / 488 レビュー

by alvaro a

2020年10月25日

El curso es bueno, falta mayor soporte por parte de los tutores para la resolución de problemas .

by Federico S

2018年3月2日

It fullfilled my expectations, and created the motivation to further increase my knowledge of ML

by NFOTABONG F Q

2017年6月14日

Good course.It would be really completed if we go on in details of different analysis algorithms

by David P G

2019年12月6日

The didactic qualities of the lecturer greatly compensate the lack of support and maintenance.

by Andrés A H G

2020年6月22日

Good but too much theory without practicing at the same time. It gets boring sometimes.

by Harshith

2019年10月30日

It was brief and comprehensive , Got to learn various technologies like Knime and Spark

by Ripunjay K

2020年1月24日

Needed more clear instructions in each module else a very good course to understand ML

by Gabriel T

2018年2月3日

The course was great. Lost of great content, pedagogically sound! I leaned a whole lot

by Kairsten F

2016年12月5日

This was a good introductory class to machine learning, but I wish it had more depth.

by Gokul K

2020年8月5日

Mentors please reply in the discussion forums so that we can clear our doubts

by Jumled L

2021年2月19日

Buen curso para iniciar el entrenamiento en logaritmos de machine learning.

by Antony C

2018年4月5日

I enjoyed learning theory and technical knowledge and tools used within ML.

by Shunichiro M

2017年1月7日

Easy to follow. Good resource to understand the basic concept of big data.

by Jin L

2021年8月9日

Great course but hard to hear from the instructors with questions raised.

by John F P

2020年9月5日

Buen curso, un poco más de análisis en los ejercicios. Pero buen curso.

by Ashish A

2017年10月4日

Good coverage of concepts and hand's on. More Hands-on can be included.

by Muhammad T

2017年7月17日

it great course and it help me a lot to understand Machine Learning.

by Laurent C S

2019年7月6日

great course, all examples with Spark and Knime were working for me

by Chaitanya J

2019年4月9日

Very good course but not getting course certificate. Please help!

by Nicolas I

2017年2月11日

I think its a good introductory course, but lacking in exercises.

by Juan J R M

2017年6月27日

It's necessary to get in some themes deeper to understand more

by Harsh O

2018年8月11日

The course was really informative .I got new things to learn.

by Huber M

2019年9月19日

Thas good course for learn the machine learning and big data

by 李诗瑶

2020年10月7日

It seems that there are problems with the dataset of Spark.

by Velavan S

2020年8月27日

The course is easy. Expected more algorithm detailing.