adgehbirhane/Amharic-Sentiment-Analysis

``` SENTIMENT ANALYSIS FOR AMHARIC LANGUAGE ``` (Fundamentals of Machine Learning class project. ) ## 1. Introduction ### 1.1. General Description Sentiment analysis is used to analyze raw text to drive objective quantitative results using natural language processing, machine learning, and other data analytics techniques. It is used to detect positive or negative sentiment in text, and often businesses use it to gauge branded reputation among their customers. Natural language processing (NLP) refers to the branch of computer science—and more specifically, the branch of artificial intelligence or AI—concerned with giving computers the ability to understand text and spoken words in much the same way human beings can. NLP combines computational linguistics—rule-based modeling of human language—with statistical, machine learning, and deep learning models. Together, these technologies enable computers to process human language in the form of text or voice data and to ‘understand’ its full meaning, complete with the speaker or writer’s intent and sentiment. NLP drives computer programs that translate text from one language to another, respond to spoken commands, and summarize large volumes of text rapidly—even in real time. NLP also plays a growing role in enterprise solutions that help streamline business operations, increase employee productivity, and simplify mission-critical business processes. Several NLP tasks break down human text and voice data in ways that help the computer make sense of what it's ingesting. One of these is the ability of the machine to understand natural languages or Natural Language Understanding (NLU). In this project we will try to build a machine learning model that will perform a sentiment analysis on Amharic language. ### 1.2. Project Justification / Motivation We are under development of Amharic Book store website. In this website all users will give comments or sentiments on their fillings about the uploaded books. The prob …