Learn and Implement Your Own Custom Machine Learning Algorithm
on Top of SAP®'s HANA® In Memory System
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 surprising result, it is based out of the probabilistic model and can outperform even complex ML algorithm.
In this course are going to start from 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.
- Prerequisite : Machine Learning Basic and Introduction With Naive Bayes
- Sprint 4.2 - Machine Learning Model Maths and Implementation on GCP