Data Science Project
MOVIE RECOMMENDER
I built a movie recommender system for movies on IDMB using data of ratings, description and genres from a data set of 1000 movies. The movie recommender returns the top 5 movie you are likely to find interesting and enjoy based on you imputing the name of one movie you enjoyed. the code to this recommender was written in python programming language and the data set was gotten from kaggle.com. You can find below a link to the python code on my GitHub repository
A picture showing its top 5 recommendations for a user who liked the movie ''Kingsman The:Secret Service''
Tweet Stalker
Have you ever wanted to know more about a person on twitter before you engage them? Do you want to have an idea of the personality of your favourite tweep? Or do you want to just have an idea of how you come off in your tweets?. The tweet stalker is a data science project that uses the power of NLP and analyzes the last 1000 tweets of any username you input inside and perfoms a sentiment analysis on their tweets. You also get to see frequently used words and phrases in a wordcloud.
Loan Prediction
Ever wondered how banks predict the amount of loan you ca have access to. Check out this machine learning end-to-end model that predicts that can help predictions using linear regression and random forest.
Leaves image classification
This project uses SVM to classify 3 different agricultural leaves commonly used in Nigeria. Helping farmers, sellers and people not too familiar with the distinction between the leaves classify such leaves by simply uploading a picture of it.
Iris flower Variant classifier
The iris flower has three major variants hat are differentiated from each other by widths and lengths sepals and petals. Using KNN I was able to create a classifier to help differentiate between the variant when the dimensions are known. This an end-to-end project that includes a deployed web app.