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Scalable Machine Learning on Big Data using Apache Spark(으)로 돌아가기

IBM 기술 네트워크의 Scalable Machine Learning on Big Data using Apache Spark 학습자 리뷰 및 피드백

1,233개의 평가

강좌 소개

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) or similar or similar for optional lectures...

최상위 리뷰


2020년 3월 25일

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.


2019년 12월 11일

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.

필터링 기준:

Scalable Machine Learning on Big Data using Apache Spark의 316개 리뷰 중 201~225

교육 기관: César A C

2020년 4월 26일

Very precise examples of parallel process to make predictions but may be not as demanding as other courses. The exercises where too easy.

교육 기관: Jasper v H

2020년 7월 24일

Good introduction to Spark, but very little playing around with ML.

Also, the UI for IBM Watson keeps changing and is really frustrating.

교육 기관: Diego D

2020년 7월 12일

This course is outdated, and there are a lot of errors in the presentation.

I think most of the videos in the course need to be updated.

교육 기관: Cristian M

2020년 11월 6일

Quite difficult to understand, since the videos have plenty of errors and the tutor goes really fast with no explanations some times.

교육 기관: krishna k

2021년 6월 3일

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

교육 기관: Shivam S

2020년 11월 22일

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

교육 기관: Sanders L

2020년 11월 19일

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 Video content seems to be outdated and not delivered in a format consistent with other IBM courses.

교육 기관: Ratnakar M

2020년 1월 16일

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

tutor took . Thanks

교육 기관: TJ G

2020년 1월 11일

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

교육 기관: Binod M

2020년 8월 11일

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

교육 기관: Aleksei K

2020년 1월 22일

Hard to listen video without subtitles.

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

교육 기관: ARSHAD S A

2020년 6월 27일

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

교육 기관:

2021년 3월 5일

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

교육 기관: GUSTAVO E Z

2020년 10월 25일

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

교육 기관: Michael E

2020년 2월 3일

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

교육 기관: Abrar J

2020년 5월 23일

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

교육 기관: Regi M

2020년 6월 15일

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

교육 기관: Jahed N

2022년 2월 8일

Too less material and exercise for PySpark. Some interesting statistical explanations

교육 기관: Jacobo D L

2020년 10월 18일

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

교육 기관: Jason A

2020년 2월 4일

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

교육 기관: Bhaskar N S

2020년 4월 4일

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

교육 기관: Vitor A

2020년 6월 5일

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

교육 기관: Pravin K

2020년 7월 21일

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

교육 기관: Sascha B

2020년 7월 26일

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

교육 기관: Emanuel N

2021년 1월 29일

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