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Retour à Scalable Machine Learning on Big Data using Apache Spark

Avis et commentaires pour d'étudiants pour Scalable Machine Learning on Big Data using Apache Spark par IBM

971 évaluations
244 avis

À propos du cours

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...

Meilleurs avis


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.

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126 - 150 sur 243 Avis pour Scalable Machine Learning on Big Data using Apache Spark

par Ilham R

Aug 02, 2020

this is a complicated course especially for beginners

par fulvio c

Jun 09, 2020

The lines of code provided are extremely valuable.

par Utkarsh B

Jan 16, 2020

There should be some more exercises for practice.

par Devarshi G

May 10, 2020

Would've loved if more practice tests were given

par Harshit K L

Mar 10, 2020

The Course can be made to cover some more basics

par Valerio R

Feb 01, 2020

Please less math calculus in the quitzzes

par ycey

Jan 07, 2020

Need to be more organized course items

par REN F

Apr 05, 2020

Environment never get set up properly

par Daniel J B O

May 27, 2020

Good refresh of Apache spark

par LIN J

Jun 10, 2020

Video is too blur

par Tchuya P A

Mar 22, 2020

très intéressant

par Narendra b O

Dec 24, 2019


par Anna A

Apr 17, 2020

If you have some experience with python or ML - it is an easy course to follow but seems not to be deep enough. If you are begginer in these field I do not reccomed the cource.

Not really systematic. The only thing it does: of you have and experience with python and ML it let you taske Spark. But all you skills seems to be not really used. Also the concepts of sparks seems to be hardly touched. I would call the course "Hello world"

if you are a begginner: you will not learn about ML or python. Some concepts are explained on simlpfied level that could lead to misleading.

Tests and actual topic seems to be unrelated

par Vladimir G

Jan 19, 2020

Good day whoever reads this!

First of all I'd like to say thank you for the course. This topic is pretty interesting for me and I move through this course with interest. IF you would update videos according python 3.6++ as in notebooks it would be much easier to learn and get into things. Also final assignment seems a too easy.

Also quality of sound and videos varies from week to week, and sometimes even from lesson to lesson during one week.

Good day and best luck!

par antonio g

May 05, 2020

In my opinion, the quality of the videos is not good, and while the teacher explains sharing his display, the display is fog and it is so difficult to see what is doing with the code.

In addition, some classes are recorded from a teacher´s car, I may understand that in some countries it could be usual, but in another one is a signal of non-professional behaviour.

par Julian S

May 09, 2020

Its only a part of a longer course. I would have prefered the longer version without getting the feeling of missing half of the story. The final Project did not feel like i did it my self. The answers of the last to questions in the correspondig test where strange (wrong?). Nevertheless I got the feeling that the full course would have been really nice ;)

par Debayan P

Jun 05, 2020

The Course is complicated to understand for beginners. The introduction and many concepts could be more clarified at a slower pace. It would be better if the instructor could use a bit more time to teach the concepts and explain the concept of the Spark environment in general. Otherwise, the instructor has put a valiant effort.

par Bo T

Mar 29, 2020

Some of the content could have been presented more clearly and recorded in the same manner consistently, few items seemed to repeat also while other are not covered well. The code walk thought should have been better explained and with less errors/clarifications which are later explained through video quiz or overlays.

par Mitchell H

Jun 08, 2020

Good for learning the fundamentals of Spark, but unfortunately this course is becoming out of date. Many of the lectures need to be completely re-rerecorded to keep up with the evolution of spark. The quizzes are painfully easy and don't reinforce enough of the code. Needs more coding assignments. All in all, it's OK.

par Jesus M G G

Dec 26, 2019

-Some videos seem outdated, and one of them doesn't have all subtitles.

-The exercises sometimes uses some models or functions not covered in the videos

-I had some issues connecting to the Spark Kernel (it was working before and then stop working. It fixed it self after a few days)

par Shivakumar K H

Apr 22, 2020

I felt that the course was filled with practicals which was explained very fast and without proper explaination. But the overall content was really good. It must have been more than 4 weeks and with proper explaination on coding part and including more related theories.

par Mohammad S H

Apr 06, 2020

i like very much the Machine Learning, but the course was focusing to cover the whole functions,methods,logarithms...

but i was preferred to focus on few concepts and do more practicing on to understand more the course and to make it more beneficial in our job carrier.

par Dylan W

May 21, 2020

I think this is a fine introduction to Apache Spark, but the notebooks don't really require much thought to complete. It'd be nice if they were a bit more instructive. And I'm not a big fan of lecture videos just showing the instructor type the code.

par Scott P

Feb 27, 2020

The course material was clear but we are never really given any challenging practice exercises to do. The "project" at the end was litterely just running prewritten code - it would have been better if we got to write the code on our own.

par Rashmin D

Apr 22, 2020

Its a good course but it duplicated content from the previous course in this specialized certification. Also speed for writing code is too fast in video. But some APIs and exercises are really good.