To stay competitive, organizations have started adopting new approaches to data processing and analysis. For example, data scientists are turning to machine learning. Our Machine Learning Course offering, Apache Spark teaches you processing of massive amounts of data using Apache Spark’s distributed compute capability and its built-in machine learning library.
This intensive Machine Learning Course, Apache Spark training, provides an overview of data science algorithms as well as the theoretical and technical aspects of using the Apache Spark platform for Machine Learning. This training course is supplemented by a variety of hands-on labs that help attendees reinforce their theoretical knowledge of the learned material.
We also offer R Programming Machine Learning Course which has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning.
Sign up today for one of our instructor led Machine Learning Classes and Learn Machine Learning now.
Our Machine Learning courses continues to be in high demand. The popular courses are:
- Machine Learning with Apahe Spark Training
- Learn Data Science, Statistics, and Machine Learning using Python
- R Programming Training
Our Machine Learning Course, Machine Learning with Apache Spark Training, covers following topics:
- Machine learning algorithms
- Introduction to functional programming
- Introduction to Apache Spark
- The Spark Shell
- The Spark Machine Learning Library
- Text mining
Our Machine Learning Course, R Programming Training, covers following topics:
- Working with R
- R Syntax
- R Data Structures
- Control Statements
- Input / Output
- Data Import and Export
- R Statistical Computing Features
- Data Visualization
- Data Science Algorithms and Analytical Methods
You can also Learn Machine Learning from our popular machine learning webinars:
Web Age Machine Learning Training can be delivered in traditional classroom style format. You can also Learn Machine Learning via our courses delivered in a synchronous instructor led format.
- Applied Data Science and Business Analytics
- Machine Learning Algorithms, Techniques and Common Analytical Methods
- Apache Spark Introduction
- Spark’s MLlib Machine Learning Library
This Apache Spark training course has 3 hands-on labs that are outlined at the bottom of this page. The labs cover the spark-submit tool as well as Apache Spark shell. The labs allow you to practice the following skills:
Lab 1 - Using the spark-submit Tool
Spark offers developers two ways of running your applications:
- Using the spark-submit tool
- Using Spark Shell
In this lab, we will review what is involved in using the spark-submit tool.
Lab 2 - The Apache Spark Shell
Interactive development environment in Spark is provided by the Spark Shell (also known as REPL: Read/Eval/Print Loop tool) that is available for Scala and Python developers (Java is not yet supported).
The lab instructions below apply to the Scala version of the Spark Shell.
Lab 3 - Using Random Forests for Classification with Spark MLlib
In this lab, we will learn how to use Random Forests implementation of the algorithm from Spark's Machine Learning library, MLlib, to perform object classification.
Random Forests algorithm is regarded as one of the most successful supervised learning algorithm that can be used for both classification and regression.
In our work we will use the Python version of the library, which provides API similar to those implemented in Scala and Java.
We will also use the spark-submit Spark tool to submit the application from command line rather than typing in commands in Spark Shell.
Web Age Spark class can be delivered in traditional classroom style format. This Apache Spark Training can also be delivered in a synchronous instructor led format.
Data Scientists, Business Analysts, Software Developers, IT Architects
Participants should have the general knowledge of statistics and programming