Wycliffe Mwebi

Natural Language Processing(NLP) Portfolio

	Project Name	Description	Project Link
1	PRE-PROCESSING TEXT DATA -How to prepare text data for machine learning	Machines cannot understand English or any text data by default. The text data needs a special preparation before you can give it to the machine to predict something out of it. In this project, I will practically go through all the required steps such as removing stops words, correcting spelling mistakes, removing meaningless words, removing rare words and many more.	Link
2	SENTIMENT ANALYSIS -Amazon Customer	Sentiment analysis is an NLP technique used to determine whether data is positive, negative or neutral. In this project, I will create an NLP machine learning model to predict if a new incoming Amazon customer review is positive or negative.	Link
3	SENTIMENT ANALYSIS -Daily News	This project attempts to analyze the daily news we are subjected to and tries to investigate the sentiments associated with the news articles. It also tries to investigate if there is a perticular trend in the way the major publishishers from around the world report stories.	Link
4	TOPIC MODELLING -BBC News Articles	Topic modelling is an NLP technique used to determine the topic of a set of documents based on the content. In this project the task is to identify major themes/topics across a collection of BBC news articles.	Link
5	ARTICLE SUMMARIZER -Wikipedia articles	Text Summarization is one of the techniques used in NLP to create short meaningful collection of text summaries from text resources like articles, books, research papers or even a webpage. In this project the task is to summarize wikipedia articles.	Link
6	ARTICLE SUMMARIZER - Medicine Descriptions	Text Summarization is one of the techniques used in NLP to create short meaningful collection of text summaries from text resources like articles, books, research papers or even a webpage. In this project the task is to summarize Medicine Descrptions provided in the file named 'TASK.xlsx'	Link