Introduction to Machine Learning With SAP® HANA®
Learn and Implement Your Own Custom Machine Learning Algorithm on Top of SAP®'s HANA® In Memory System
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Ajay Nayak
Machine learning and the world of artificial intelligence (AI) are no longer science fiction. They’re here!
Get started with the new breed of software that is able to learn without being explicitly programmed, machine learning can access, analyze, and find patterns in Big Data in a way that is beyond human capabilities. The business advantages are huge, and the market is expected to be worth $47 billion and more by 2020.
In this course, you will implement your own custom algorithm on top of SAP®'s HANA® Database, which is an In-Memory database capable of Performing huge calculation over a large set of Data. We are going to use Native SQL to write the algorithm of Naive Bayes. Naive Bayes is a classical ML algorithm, which is capable of providing a surprising result, it is based out of the probabilistic model and can outperform even complex ML algorithm.
In this course, we are going to start from the basics and move slowly to the implementation of the ML algorithm. We are not using any third party libraries but will be writing the steps in the Native SQL, so our code can take advantage of HANA® DB in-memory capabilities to run faster even when Data Set grows large.
What knowledge & tools are required?
Who should take this course?
What will students achieve or be able to do after taking your course?
Introduction to Machine Learning
Why Machine Learning and Problem Solving Techniques
Problem solving techniques in ML and Intro to Naive Bayes
A Basic Approach to Solving Sentiment Analysis Using Naive Bayes Part-1
A Basic Approach to Solving Sentiment Analysis Using Naive Bayes Part-2
Language Used for Implementing NB Algorithm
All development Code and Repositories:
Creating the Procedure
Extracting Words From Test String
Calculating Posterior Probability Using NB Part-1
Calculating Posterior Probability Using NB Part-2