Final Year project based upon Network Intrusion Detection System
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Updated
Jul 10, 2019 - Jupyter Notebook
Final Year project based upon Network Intrusion Detection System
Sentiment Analysis of Movie Reviews is either positive or negative review, the dataset which is used is "IMDB Dataset of 50K Movie Reviews" and the machine learning algorithm which I used in this is Logistic Regression , Random Forest and LinearSVC.
Implementation of various Machine Learning and Deep Learning models for Sentiment Analysis on the 'Sentiment Labelled Sentences Data Set' by University of California, Irvine.
Text classification on job description dataset
Application of various text classification algorithms on multiple datasets.
Object Detection Techniques for the Vehicle Detection
Arabic_Dialect_Identification_NLP-AIM-Task
Fake news detection using TF-IDF vectorization and LinearSVC
A flask app to prdict iris flower using LinearSVC deployed on heroku
The objective of this project is to classify whether upcoming product will have positive or negative Sentiment.
NLP using SpaCy python library
This project was built within 24h by the team Augusteam for the DevHacks 2022 Climate Change hackathon sponsored by Systematic and it won the third place worth 500€
Machine Learning clasificación con SKLearn
This is a simple project which trains on the datasets, based on the tweets of US President Donald Trump and Canadian Prime Minister Justin Trudeau and predicts which one belongs to whom?
This project involves the implementation of efficient and effective LinearSVC on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.
Part of an internal project for my internship
DevStack Solution Internship Program "Data Science Internship" Task-1 on Fake news detecting system using python and machine learning
This project aims to determine the likelihood of a company facing bankruptcy, a crucial aspect of financial analysis and investment decision-making.
Scraping data through Instagram and using the data to build a predictive model
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