Sentiment analysis and forcasting using Amazon SageMaker

Introduction

Machine Learning has emerged to be one of the most sought after technologies in recent times. Amazon SageMaker is a fully managed machine learning platform in the cloud. It is an AWS service that can help you to analyze data and then and build, train, and deploy machine learning models in the cloud. SAP HANA is a business data platform. It is an in-memory relational database. SAP HANA's Python library contains a data frame which can be used to read data from a HANA instance and then examine the data inside a SageMaker notebook.

Potential Use Cases

Assume that you have millions of records in the database. You now need to predict or forecast based on the data you have. Here's exactly where you can leverage Amazon SageMaker to do the analysis and forecasting for you. SageMaker can be used in predictive analysis, medical image analysis, predictions in sports, marketing, climate, etc. You can also take advantage of Amazon SageMaker for detecting frauds in banking as well.

Sentiment analysis

You can take advantage of sentimen analysis to predict the behavior patterns of an individual. As an example, data from the Facebook can be used for sentimental analysis to understand the mood, emotions of individuals and then send out alerts if need be. A piece of writing of an individual can contain negetive thoughts and AI can be used here to predict the future moods of that individual. There can be an individual who might develop suicidal thoughts - data from social media like Facebook can be used to understand the behavioral patterns and then send out alerts to that person's contacts. After reading the data, you'll have to train a model and then use an algorithm to predict the future possible moods of the individual.

Sentiment analysis using Amazon SageMaker

In this section, we'll examine how we can take advantage of Amazon SageMaker for sentiment analysis. Sentiment analysis is a technique that uses the emotional tone used in words to understand the attitude, emotions expressed. This can be very helpful in many scenerios. The ability of Amazon SageMaker to easily build, train, and deploy machine learning models at any scale can be very helpful to build an application that has these capabilities.

Summary

Amazon SageMaker can help you build machine learning models with ease. SageMaker can be a great choice for pattern detection, forecasting, etc.