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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 IBM

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1,232 calificaciones
313 reseña

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.

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126 - 150 de 315 revisiones para Scalable Machine Learning on Big Data using Apache Spark

por Rich P

3 de sep. de 2020

It was surprisingly fast-paced. There were a few intuitive leaps, including a bad data reference on the final project, that were potential stumbling blocks, but I feel more confident having overcome them.

por Sourab M

6 de abr. de 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.

por Miele W

2 de ene. de 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 :)

por Dhivyarupini R

11 de jul. de 2020

Teaching was clear and understandable. Only feedback would be I hope the lab work would be more hands on because I'm worried I don't pick up the concepts unless I type them out.

por Ihsandi D

23 de ene. de 2021

Depending on the student, this can either be an easy or a difficult course. Some parts needs update, and it would be great if there are more explanation on the algorithms.

por Robert v d V

16 de jul. de 2020

Nice introduction to Big Data processing, No coding skill required. A little more focus on the theory would be nice as the Python coding exercises are a little redundant.

por Giorgio G

20 de may. de 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).

por Zaheer U R

1 de jun. de 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.

por Leonardo D

24 de feb. de 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.

por Julien P

9 de jun. de 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.

por Chokdee S

4 de may. de 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

por Brandon C

18 de feb. de 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.

por Stefan W

22 de ene. de 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.

por Shahtab A K

26 de jul. de 2020

In some videos, it shows one thing in the video and then there is a prompt to follow another one. It gets a little bit confusing there.

por Itamar A T

28 de mar. de 2020

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

Thanks for the dedication in helping us.

Itamar

por Shashank S

23 de feb. de 2020

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

por Sarath C G K

16 de abr. de 2020

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

por Lawrence K

4 de abr. de 2020

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

por shanmukha y

12 de abr. de 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" : )

por Stephane A

1 de may. de 2020

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

por No O

2 de feb. de 2020

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

por yan l

17 de jun. de 2020

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

por Daxkumar J

21 de feb. de 2020

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

por JOSE J M C

25 de may. de 2020

Instructor pronunciation is not the best for someone who are not usually listening explain so fast.

por Jochen G

15 de ene. de 2020

Cool course with a slow paced start and then interesting examples to work with Apache Spark ML.