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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

3.9
별점
920개의 평가
232개의 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) 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...

최상위 리뷰

CL

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.

M

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 231개 리뷰 중 201~225

교육 기관: Leon B

May 15, 2020

Learn about the diffs between rel-databases, no-sql and blobs on disk. Learn (again!) what mean, stdev, median and kurtosis mean. Plotting with MatPlotLib, brought as the 1st world wonder.

Intro to Spark and your final challenge: execute a provided notebook and just copy-paste the results.

No need to think, just know how to apply CTRL-C & CTRL-V in the end.

Al in all, can be done on a rainy Sunday afternoon instead of 4 weeks.

교육 기관: Alexander D

Mar 13, 2020

Don't take this course. It's poorly made, and should not be a part of this specialization unfortunately. I do like the subject matter, but the IBM cloud framework is a headache. I struggled with it and barely passed the final project because some cells wouldn't run.

I did do what I could to absorb the information by looking at the notebook and testing myself, but to be honest, I just wanted to get it over with.

교육 기관: Timur U

Mar 29, 2020

The course - Scalable Machine Learning on Big Data using Apache Spark has too complicated instructions for Labs. This course should be more properly organized like another part of IBM Professional Certificate, Intermediate Level - Machine Learning with Python. I don't understand why this course was included to this certificate. I'm not motivated to continue this course.

교육 기관: Alexander W

May 21, 2020

The course is a patchwork of incoherent and outdated videos, apparently mostly reused from other courses. Additionally most videos already contain retroactively added comments correcting, mistakes or outdated content. In my opinion it should be obvious that this course requires a complete makeover with updated videos.

교육 기관: Jafar P

Jul 28, 2020

This course could be much better. It is not as clear and explained as the first one "Machine learning with Python". It would be good to keep the same way of explaining. It should be "easy" to understand for someone who has never studied AI before (which is the case for the first course).

교육 기관: Tong J

Apr 22, 2020

Compare with the other course in this professional certificate, this course didn't provide clear information to people want to learn. I spend very tough time on this course comparing to the other courses, I just recommend someone make a better spark course to replace this one.

교육 기관: Eric

Jan 20, 2020

The instructor breezed through course preparation and gave lectures from his car. Very easy course that doesn't challenge you or hold you to any standard of learning. One would be better off learning from YouTube and Apache Spark guides. Don't pay for this course!

교육 기관: Irfan S

Jul 14, 2020

Worst course i have ever took in Coursera. I would request IBM to replace this junk course from IBM AI specialization. This course doesnt teach BigData and neither teach Apache Spark. Too some extent it covers Machine Learning.

교육 기관: Ashutosh K

Apr 22, 2020

very very superficial, there is no way anyone can learn apache spark. I feel like I have wasted so much time but not learnt anything at all. Really disappointing stuff from coursera

교육 기관: Li

Apr 20, 2020

Poor delivery of course material, even worse video.

Instruction on quiz and assignments confusing.

You may get a bit hands-on experience of Spark but you LEARN nothing substantial.

교육 기관: Pierre-Antoine M

Apr 20, 2020

Started nice with the first two "weeks". But week 3 and 4 are jokes with little to no content and final project is just running a pre-existing notebook and reading results

교육 기관: Nauman A S

Aug 04, 2020

HEY, TO BE HONEST, I DID NOT LIKE THE TEACHER DUE TO MANY REASONS: 1. HIS VAGUE ACCENT, 2. HIS SPEED WHILE PRACTICINF CODE WAS HIGH AND STUDENT DO THE PRACTICE MEANTIME

교육 기관: Karim F U

May 04, 2020

Very poor content quality, nothing to do with the quality of the first module.

new and complex concepts are assumed to be known from the get go.

교육 기관: Rodrigo F

Jul 16, 2020

Can`t believe this module was part of the course. very hard to follow. This course needs to be updated asap. what a waste of time.

교육 기관: Mohammed K

Jul 06, 2020

This course is outdated, topics unclear, I had to jump to Udemy and Udacity to learn Spark.

Hope to see this course updated, Thanks

교육 기관: Sebastian W

Apr 19, 2020

This guy should never teach any person at all.

The videos are very bad processed and the exercises are very bad documented.

교육 기관: Oussama B

Feb 25, 2020

I am really disapointed by this chapter!!!! I learnd nothing, week 2 evaluation is ridiculous I did it with Excel....

교육 기관: Kovács R

Feb 23, 2020

Low-quality videos, not relevant quiz questions. I can set up the same course in one day. Waste of time.

교육 기관: Berkay K

Jun 19, 2020

Hard to understrand teacher. Content of this course unfortunatly not enough for learning.

교육 기관: Parijat K

May 03, 2020

The course didn't live up to the expectation. Very little explanation. Too superficial.

교육 기관: Raul S C

Feb 28, 2020

muy malo por eso me di de baja de todos los cursos ni si quiera están las traducciones

교육 기관: Nissim l

Apr 17, 2020

Instructed with python 2.7 -old material they didn't bother to update.

NOT OKAY!!!

교육 기관: Wasim m m

May 22, 2020

the worst course by ibm

my confidence level goes down after taking this course

교육 기관: Yutaka R

May 25, 2020

If the video without subtitle, I swear I can't understanding the lecture....