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15-python-problems-easy-to-difficult

analysis-of-job-changes

analyzing-restaurant-reviews-using-nlp

this is just a basic nlp. can analyze sentiment from simple reviews. requires more tuning.

breast-cancer

c-and-cpp-codes-from-basic-to-advanced

This repo contains all my C and C++programming codes I did throughout my university life. therefore it contains basic codes as well as advanced codes.

emotion-detection-from-textual-data-using-nlp-feature-extraction-techniques-and-ml-classifiers

this model was prepared for my undergrad thesis.

exploratorydataanalysis_cardiovascular_disease

Here I've used the dataset from Kaggle

fraud-detection

hakcerrank-problem-solving

heart-failure-prediction

this is a personal project using ML techniques. downloaded dataset from Kaggle.

hostel-management-system

This project was done by me and my partner for our software development course back in 2018

house-price-prediction

Did this project using data from Kaggle. Also, submission1.csv file contains the predicted result

identifying-spam-messages-using-nlp

implementing-linear-regression-from-scratch

medical-appointment-showup-no-show

the objective of this project is to analyze medical data to predict if a patient is going to show up for his appointment or not. I tried to understand what are the factors behind this reason. there are 14 features and 8 of them seemed like to have a relation with a patient's attendance.

ml-using-iris-dataset

finished up a book regarding ML using iris dataset and I coded along the book...thought it'd be nice to upload it on my github :-)

movie-recommender-v2

movie_recommender

nlp-beginner-steps-using-playstore-reviews

this project shows some compulsory things related to nlp such as preprocessing, training and evaluating model.

nlp-in-python-tutorial

comparing stand up comedians using natural language processing

predicting-different-types-of-glass

predicting_titanic_survivor

It was the very first problem I've solved in Kaggle. Also, dataset is from Kaggle

sentiment-analysis-of-movie-reviews

It was a small and basic sentiment analysis project. Used Vader to get the polarity of sentences. Then using the polarity score I calculated comp_score and compared it with the actual label of the review and calculated the accuracy. Before completing my undergrad thesis (which was also related to nlp), I did couple of small projects like this to get a better understanding of nlp.

suicide-data-analysis

udaconnect-message-passing