
Local, instructorled live Apache Spark MLlib training courses demonstrate through interactive discussion and handson practice the fundamentals and advanced topics of Apache Spark MLlib
Apache Spark MLlib training is available as "onsite live training" or "remote live training" Onsite live training can be carried out locally on customer premises in Lithuania or in NobleProg corporate training centers in Lithuania Remote live training is carried out by way of an interactive, remote desktop
NobleProg Your Local Training Provider.
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Testimonials
This is one of the best hands-on with exercises programming courses I have ever taken.
Laura Kahn
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
Richard is very calm and methodical, with an analytic insight - exactly the qualities needed to present this sort of course.
Kieran Mac Kenna
Course: Spark for Developers
We know a lot more about the whole environment.
John Kidd
Course: Spark for Developers
The trainer made the class interesting and entertaining which helps quite a bit with all day training.
Ryan Speelman
Course: Spark for Developers
I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.
Course: Spark for Developers
Ernesto did a great job explaining the high level concepts of using Spark and its various modules.
Michael Nemerouf
Course: Spark for Developers
Richard was very willing to digress when we wanted to ask semi-related questions about things not on the syllabus. Explanations were clear and he was up front about caveats in any advice he gave us.
ARM Limited
Course: Spark for Developers
The VM I liked very much The Teacher was very knowledgeable regarding the topic as well as other topics, he was very nice and friendly I liked the facility in Dubai.
Safar Alqahtani - Elm Information Security
Course: Big Data Analytics in Health
Small group (4 trainees) and we could progress together. Also the trainer could so help everybody.
ICE International Copyright Enterprise Germany GmbH
Course: Spark for Developers
Ajay was very friendly, helpful and also knowledgable about the topic he was discussing.
Biniam Guulay - ICE International Copyright Enterprise Germany GmbH
Course: Spark for Developers
The lab exercises. Applying the theory from the first day in subsequent days.
Dell
Course: A Practical Introduction to Stream Processing
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
Applicable scenarios and cases
zhaopeng liu - Fmr
Course: Spark for Developers
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case analysis
国栋 张
Course: Spark for Developers
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all parts of this session
Eric Han - Fmr
Course: Spark for Developers
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I liked the methodology expected by Jorge
Experian Colombia S.A
Course: Spark for Developers
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This is one of the best quality online training I have ever taken in my 13 year career. Keep up the great work!.
Course: Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP
I think the trainer had an excellent style of combining humor and real life stories to make the subjects at hand very approachable. I would highly recommend this professor in the future.
Course: Spark for Developers
The trainer was passionate and well-known what he said I appreciate his help and answers all our questions and suggested cases.
Course: A Practical Introduction to Stream Processing
Apache Spark MLlib Course Outlines in Lithuania
It divides into two packages:
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spark.mllib contains the original API built on top of RDDs.
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spark.ml provides higher-level API built on top of DataFrames for constructing ML pipelines.
Audience
This course is directed at engineers and developers seeking to utilize a built in Machine Library for Apache Spark











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