Online or onsite, instructor-led live Apache Spark MLlib training courses demonstrate through interactive discussion and hands-on practice the fundamentals and advanced topics of Apache Spark MLlib.
Apache Spark MLlib training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Onsite live Apache Spark MLlib training can be carried out locally on customer premises in Kathmandu or in NobleProg corporate training centers in Kathmandu.
NobleProg -- Your Local Training Provider
Kathmandu Classroom
near Soaltee, Tahachal Marg, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Tahachal Marg with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
Thamel Classroom
near Radisson , Ward 2, Kathmandu, Nepal, 44600
Set in Kathmandu, this classroom is well located near Thamel, with all amenities and WiFi.
For Sales Enquires and Meetings
All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.
This course is intended for developers and data scientists who want to understand and implement artificial intelligence in their applications. Special focus is placed on data analytics, distributed AI, and natural language processing.
MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs.
It divides into two packages:
spark.mllib contains the original API built on top of RDDs.
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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Testimonials (2)
A lot of practical examples, different ways to approach the same problem, and sometimes not so obvious tricks how to improve the current solution
Rafal - Nordea
Course - Apache Spark MLlib
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
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