top of page

Projects

TWITTER TOPIC MODELLING

I scraped text data off Twitter using Tweepy to discover the hidden topics and relationships between each tweet with the use of Topic Modelling; an unsupervised algorithm. Once a topic a discovered, a suggested link is given to read more about it. Project link

topic-modelling.png

SUPER BOWL ADS ANALYSIS

Loaded data was preprocessed by removing null & duplicates values , column renaming and data type conversion for the purpose of feature engineering and data analysis for the recommendation of companies with the lowest cost of investment. Project link

tables_1.png

AMAZON TEXT CLASSIFICATION APP

Scraped data of Amazon reviews which was stored in a database and loaded using Python for purpose of classifying text reviews into different sentiments; positive, negative and neutral using SOTA machine learning algorithms. 

Project link

How-to-train-CNN-for-multi-label-text-classification.png
bottom of page