saranyachaganti / ML-Projects

The following repository consists of various machine learning projects of various domains

The projects in this repository are done during my 100 days of machine learning challenge.

List of Projects :

1) Text based classification

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/IRIS

Dataset : IRIS Dataset (UCI Machine learning repository)

Agenda : Classify the class of the type of flower given the measurements

Description : This ML Porject is a multivariate dataset based on types of IRIS flower. When we give few parameters as inputs the model predicts on which type of flower it belongs to either Iris setosa, Iris virginica or Iris versicolor

2) Loan Approval - Loan Approval project

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/Loan

Dataset : Loan prediction ( Kaggle)

Agenda : To predict the product a customer is likely to buy

Description : This project consists of deciding the output which is based on various parameters such as salary, credit history, education etc. . A detailed overview of graphs are plotted such as correlation plots, Linear plots etc. for a better intuition for exploratory data analysis

3) Market Basket Analysis

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/Market-Basket-Analysis

Dataset : Online retail ( Kaggle)

Agenda : Decide weather the person's loan can be approved or not based on a few parameters

Description : Through this project you can find intresting associations and relationships among the datasets (the algorithm ive used can also be applied to a recommendaton engine) .For example if you buy read you are most likely to buy Jam or butter or both. So the owner of the grocery store can put an offer on both combined for more sales.

4) Product Identification - Fashion MNIST project

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/Fashion-MNIST-Project

Dataset : Fashion MNIST ( Inbuilt in keras)

Agenda : Identify the item in the image

Description : The dataset has 70k+ labelled images through which when given any input it identifies it as a hat/sweater/ankle boot or something else based on the 10 classes we have

5) Sentiment Analysis - Movie review classification project

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/Movie-Review-Classification-Project

Dataset : Imdb inbuilt dataset in keras

Agenda : This project classifies the movie review as a good review or a bad one

Description : The project lso deals with a little bit of NLP domain through which we do the data preprocesssing and tune the data according to our needs. Also extended the project where you personally can give any movie review on your own and it gives out the classified output i.e: Good or Bad

6) Recommendation Engine

Code : https://github.com/saranyachaganti/ML-Projects/tree/master/Movie-Recommendation-Engine

Dataset : My github

Agenda : Recommend 5 movies based on the input you give

Description : A movie recomendation engine is like your netflix / amazon which constantly reminds you what you like and what you're going to like based on your watch list . In this project you give a movie of your choice and it reccomends 5 other movies which are related to that movie.

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