返回到 Scalable Machine Learning on Big Data using Apache Spark
學生對 IBM 提供的 Scalable Machine Learning on Big Data using Apache Spark 的評價和反饋
1,211 個評分
課程概述
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
熱門審閱
2020年3月25日
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.
2019年12月11日
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.
篩選依據：
301 - Scalable Machine Learning on Big Data using Apache Spark 的 307 個評論（共 307 個）
創建者 Nazim U S
•2021年6月27日
One of the worst course ! Struggling to understand Romeo's accent.
創建者 gurdeep s
•2020年5月25日
Not much explanation regarding concepts. Disappointed.
創建者 Arjan P B
•2020年5月3日
What a mess, please remove this course right away.
創建者 Annejet t K
•2020年6月17日
Old course not compatible with python 3.7
創建者 harshad j
•2020年9月2日
WAS not upto that
創建者 Giuseppe C
•2020年3月28日
very bad teacher
創建者 Abish P
•2020年8月14日
Not that good
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