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學生對 IBM 提供的 Scalable Machine Learning on Big Data using Apache Spark 的評價和反饋

3.8
1,219 個評分
308 條評論

課程概述

This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark. Most real world machine learning work involves very large data sets that go beyond the CPU, memory and storage limitations of a single computer. Apache Spark is an open source framework that leverages cluster computing and distributed storage to process extremely large data sets in an efficient and cost effective manner. Therefore an applied knowledge of working with Apache Spark is a great asset and potential differentiator for a Machine Learning engineer. After completing this course, you will be able to: - gain a practical understanding of Apache Spark, and apply it to solve machine learning problems involving both small and big data - understand how parallel code is written, capable of running on thousands of CPUs. - make use of large scale compute clusters to apply machine learning algorithms on Petabytes of data using Apache SparkML Pipelines. - eliminate out-of-memory errors generated by traditional machine learning frameworks when data doesn’t fit in a computer's main memory - test thousands of different ML models in parallel to find the best performing one – a technique used by many successful Kagglers - (Optional) run SQL statements on very large data sets using Apache SparkSQL and the Apache Spark DataFrame API. Enrol now to learn the machine learning techniques for working with Big Data that have been successfully applied by companies like Alibaba, Apple, Amazon, Baidu, eBay, IBM, NASA, Samsung, SAP, TripAdvisor, Yahoo!, Zalando and many others. NOTE: You will practice running machine learning tasks hands-on on an Apache Spark cluster provided by IBM at no charge during the course which you can continue to use afterwards. Prerequisites: - basic python programming - basic machine learning (optional introduction videos are provided in this course as well) - basic SQL skills for optional content The following courses are recommended before taking this class (unless you already have the skills) https://www.coursera.org/learn/python-for-applied-data-science or similar https://www.coursera.org/learn/machine-learning-with-python or similar https://www.coursera.org/learn/sql-data-science for optional lectures...

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AC
2020年3月25日

Excellent course! All the explanations are quite clear, a lot of good quality information provided from amazing teacher. Additionally, response times for any question is very fast.

CL
2019年12月11日

Really really REALLY enjoyed this course! The instructor does a masterful job of going from simple examples and building up complexity in a very logical and thorough way.

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201 - Scalable Machine Learning on Big Data using Apache Spark 的 225 個評論(共 309 個)

創建者 krishna k

2021年6月3日

Great course material, but the videos seemed to be confusing and counter productive. The videos are also old and need to be updated.

創建者 Shivam S

2020年11月22日

Not enough coding opportunities provided. More Coding assignments and practice will be better and more content is very much needed.

創建者 Sanders L

2020年11月19日

Course needs some polishing. Video content seems to be outdated and not delivered in a format consistent with other IBM courses.

創建者 Ratnakar M

2020年1月16日

Content was ok , IBM has better course production than this , sorry to say , i m very grateful for the effort

tutor took . Thanks

創建者 TJ G

2020年1月11日

This deeply need a much more detailed course on Apache Spark. You need far more than this course to actually get into PySpark.

創建者 Binod M

2020年8月11日

Good introduction but seemed rushed and felt like it had lot of gaps . But the explanations that were given were very nice

創建者 Bear B

2020年1月22日

Hard to listen video without subtitles.

It be better to show how create a notebook in the watson on the first lecture.

創建者 ARSHAD S A

2020年6月27日

It would be nice to have an updated course content video. Other IBM courses are much more updated and interesting.

創建者 Vhui77@gmail.com

2021年3月5日

Very hard to understand the instructor. The speech intonation needs to be improved as a first step.

創建者 GUSTAVO E Z

2020年10月25日

The english accent of Mr Romeo Kienzler is sometimes difficult to understand but knows the program

創建者 Michael E

2020年2月3日

There was not enough learning about how to use ApacheSpark, it was more of a show what it can do.

創建者 Abrar J

2020年5月23日

I think representation should be better and provided coding notebook should be self explanatory.

創建者 Regi M

2020年6月15日

The instructor in this course lacks thorough explanation of the topics being discussed.

創建者 Jacobo D L

2020年10月18日

would like to have the video examples codes / link to follow the exercises hands on

創建者 Jason A

2020年2月4日

more hands-on would be nice, rather than having so much of the code pre-written

創建者 Bhaskar N S

2020年4月4日

Compared to other courses in AI Engineering, this one was a bit too technical

創建者 Vitor A

2020年6月5日

Content was ok. Not many insights why Apache is better/faster than others.

創建者 PRAVIN K R

2020年7月21日

Not Clearly Understandable. Lack of Deep Knowledge provided on the course

創建者 Sascha B

2020年7月26日

Very high level, exercises could have been more challenging and hands-on

創建者 Emanuel N

2021年1月29日

Me parecio incompleto el curso. Algunos temas debieron extenderse mas.

創建者 Tarun

2020年6月1日

Concepts not explained well, have to watch videos twice to understand.

創建者 Fabio G

2021年2月10日

I would add more practise exercises as well as the intended answers

創建者 Aaditya M

2020年6月26日

Videos are outdated which makes it hard to follow along sometimes.

創建者 Wenbo Z

2020年5月26日

The contents are not well-organized and sometimes confusing.

創建者 André S M

2020年8月1日

The course is outdated. exemples in old version of spark