Chevron Left
Volver a Scalable Machine Learning on Big Data using Apache Spark

Opiniones y comentarios de aprendices correspondientes a Scalable Machine Learning on Big Data using Apache Spark por parte de Habilidades en redes de IBM

3.8
estrellas
1,233 calificaciones

Acerca del Curso

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...

Principales reseñas

AC

25 de mar. de 2020

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

11 de dic. de 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.

Filtrar por:

151 - 175 de 316 revisiones para Scalable Machine Learning on Big Data using Apache Spark

por Anaísa S

16 de dic. de 2021

Good course, but coach's English is poor and many corrections are made during presentations

por YASH K

27 de jun. de 2020

Overall its an excellent course but I think more programing exercise should be there.

por Hayagreev S

12 de sep. de 2020

Good Course! Was able to understand the complex python involved! Nice examples.

por Heetanshu R

30 de ago. de 2020

The professor's English is just hard to understand but otherwise it is good!

por HoangVan N

5 de ene. de 2021

This course is very good for me but there is a video not watch in Week 3

por Zijie

20 de may. de 2020

It would be perfect if the coding showing screen could be more clear.

por Roberto M

16 de jun. de 2020

Good course, but the instructor sometimes seems to be a little off.

por YERRAMOTHU G S

1 de abr. de 2020

TRAINER IS GOING BIT FASTER BUT HAD FUN WITH THIS COURSE THANK YOU

por Vijander S

1 de abr. de 2020

the programming environment is complex it should be explained

por Maurício C B

27 de may. de 2020

Precisa ser atualizado. Possui correções em alguns vídeos.

por Ilham R

2 de ago. de 2020

this is a complicated course especially for beginners

por Víctor M F S

14 de ago. de 2021

Quizas alguna propuesta de ejercicios menos guiados

por Fulvio C

8 de jun. de 2020

The lines of code provided are extremely valuable.

por Utkarsh B

16 de ene. de 2020

There should be some more exercises for practice.

por Devarshi G

10 de may. de 2020

Would've loved if more practice tests were given

por Harshit K L

10 de mar. de 2020

The Course can be made to cover some more basics

por Valerio R

1 de feb. de 2020

Please less math calculus in the quitzzes

por yasemin c

7 de ene. de 2020

Need to be more organized course items

por REN F

5 de abr. de 2020

Environment never get set up properly

por Daniel J B O

26 de may. de 2020

Good refresh of Apache spark

por LIN J

9 de jun. de 2020

Video is too blur

por Adrien P

22 de mar. de 2020

très intéressant

por skhapijulhossen

19 de may. de 2021

Can be better

por Narendra b O

24 de dic. de 2019

.

por Julien P

30 de dic. de 2020

Content was good even though very basic on statistics, certainly a good intro to Spark. However, final project/quiz was nearly insulting. Code was already written 100%, and most quiz questions were about copy/pasting literal output from pre-written code. Thought a mistake was made at first.

When students follow a course with a serious intent to learn, giving them a final quiz that barely tests their knowledge is a big downer, and makes students feel like they wasted their time learning all this stuff (even though they didn't). Students had proper access to all the code they needed to write 100% of the code themselves for the final quiz. Not sure why everything was done for them in the first place.