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

IBM의 Scalable Machine Learning on Big Data using Apache Spark 학습자 리뷰 및 피드백

816개의 평가
202개의 리뷰

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


Dec 12, 2019

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.


May 01, 2020

I like the example given and step by step tutorial given. The explanation of why things are the way they are designed certainly helped me understand the concept. Kudos.

필터링 기준:

Scalable Machine Learning on Big Data using Apache Spark의 203개 리뷰 중 76~100

교육 기관: Emmanuel H

Jun 22, 2020

I would like to thank Romeo for teaching me. I apologize to rate the course at 3/5. I did like the course in general but I missed the practice of it. The methodology process did not help me to learn the practice. I scored better in most quizes on the first attempting while I could not guess how the code are written. I wish I did learn to interpret or rewriting the code


교육 기관: Ravi P B

May 12, 2020

Its a nice course and good way to start Apache Spark.But I feel its a bit too fast as well as too high level for those who are pure machine learner and deep learner practitioners on jupyters and colabs,they are gonna find it bit tough and programming part will go over the head.So Goodluck.

But its a nice way to start learning a fascinating technology of Apache Spark.

교육 기관: Ahmed G

Mar 14, 2020

The material presented in the course is important for everyone looking to go into the Data Science or Machine Learning fields, but some of the examples in the earlier chapters use Python 2 and have not been updated to Python 3. The learner has to go hunting themselves in the forums for official posts on how to fix these error (they were there).

교육 기관: Artak K

Jun 27, 2020

Although this course introduced us to the very important idea: distributed and parallel processing, but I find it too broad and too high level. We didnt go deep into any of the topics, and the assignments are to easy(some of them are already done, you just have to find the correct number for the outputs and place it in quiz section)

교육 기관: Lucas I S

Dec 20, 2019

Like the format of this course, which seems more laid back. Having said that, some of the assignments had some confusing portion, but need to acknowledge this is an intermediate course and not a beginner one. I also missed the part of the explanation that Apache Spark has its own tools vs. using Python's SciKit

교육 기관: Avashen P

Apr 05, 2020

Great course. There should probably be more coding tests where submissions get you a grade like some of the other Coursera coding courses.

Some of the coding in the lectures is a bit too quick, but that's probably just for because I have never used the Apache Spark syntax before.

교육 기관: Dhaivat H P

Apr 21, 2020

Very good teaching techniques, The professor explained everything well, The sound quality was dull on 2nd week's video and the accent was a bit tricky for me but the quizzes were good and if you code with him you'll be able to understand the concepts easily

교육 기관: Sourab M

Apr 06, 2020

It is a good course for beginners in the domain of Apache Spark and Apache Spark ML. Programming assignments could have been better if they were applied to "Big Data" and not on toy datasets.

교육 기관: Miele W

Jan 02, 2020

Again a nice course that introduce you on Apache Spark Usage. Just a little suggestion, if you could insert a little tweak on how pass from spark to pandas and vice versa.

Enjoy :)

교육 기관: Giorgio G

May 20, 2020

Great tutorial overall.

Room for improvement: Fix the differences int the definition of kurtosis and skew between vide, test, examples (preferable the scipy definition).

교육 기관: Zaheer U R

Jun 01, 2020

It was a very interesting and skillful course. Thanks to IBM and Coursera for such a wonderful course. Special thanks to Mr. Romeo Kienzer for explaining it so well.

교육 기관: leonardo d

Feb 24, 2020

There are some issues with the normalization of the distribution moments. Everything else is good material to learn how to use apache-spark for the first time.

교육 기관: Julien P

Jun 09, 2020

Great notebooks. But the videos are getting old and are a bit obsolete compared to the contents in notebooks. I would have also appreciated more theory.

교육 기관: Chokdee S

May 04, 2020

Learning material is pretty good for getting started with Apache SparkML. Everyone who leaps into Scalable Machine Learning this is one of your choice

교육 기관: Brandon S C

Feb 18, 2020

I found this course incredibly beneficial. Moving forward, I would like to see a bit more explanation of concepts and few extra workable examples.

교육 기관: Stefan W

Jan 22, 2020

Course was nice and avoided peer-graded assignments (which I appreciate) but code was written in Python 2 which led to un-maintained code.

교육 기관: Itamar A T

Mar 28, 2020

I found difficult to understand the concepts, for sure I must have to review the class.

Thanks for the dedication in helping us.


교육 기관: shashank s

Feb 23, 2020

for the last assignment we should have got the opportunity to code in the notebook instead of just running it and reporting results.

교육 기관: Sarath C G K

Apr 16, 2020

He has good knowledge. Though his language is ok , He covered very important topics in very short span of time with high quality

교육 기관: Alaso L K

Apr 04, 2020

Nice course with real details and opportunities to practice. We just need some more private study to cement skills learnt.

교육 기관: Shanmukha S S Y

Apr 12, 2020

I felt the week 3 and 4 were rushed a bit. But everything else was well done. It was like a well defined "pipeline" : )

교육 기관: Stephane A

May 01, 2020

Nice course. I really understand big data and how to manipulate data in data centers. I can use better Apache Spark.

교육 기관: Paruhang K

Feb 02, 2020

Explanations could be a little more detailed. Felt like I was missing chunks of information while watching videos.

교육 기관: yan l

Jun 18, 2020

very systematic way to learn ApacheSpark (esp pyspark). It would be helpful to include more hands on excercise

교육 기관: Daxkumar J

Feb 21, 2020

This course gives you a basic idea behind the pyspark. If you are a beginner so this course for you.