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sonalishanbhag28

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Datasets for practice.

Fake-News-Analyzer

A Python application to recognize and filter out incorrect and misleading information about COVID-19 in the form of clickbait and fake news articles. Comparative analysis of classification results using Logistic Regression, Naive Bayes, Decision Tree, Random Forest, SVM, SGD, Count Vectorizer and KNN.

Jupyter Notebook

AI-Proctoring-Server-Side

An Online Class Student Analyser using Python to provide online instructors insight about the concentration level of students during class by using Convolution Neural Networks to detect prolonged eye closure, yawns, gaze direction and perform an environment analysis to sense distractions and cell-phones during class time. The analysis is done on screenshots from recorded class sessions.

Jupyter Notebook

Automated-Notes-Taker

NLP-based Application that aims to convert online class recordings into simple and concise summaries by using Hybrid Text Summarization- a combination of abstractive and extractive methodologies. Summarization is done using Sentence Feature Scoring and subsequent Defuzzification.

Python

Employee-Attrition-Predictor

Analysis of Employee Turnover Rate of a company by building Logistic Regression model and Random Forest Classifier, validated by 10-Fold Cross Validation, completely coded on Python. Conduction of investigation into most influential factors for turnover and exploratory Visualization (seaborn, matplotlib) based on prediction results. Application integrated with IBM Cloud to be deployed as an API.

Jupyter Notebook

Weather-Forecast

Multi-variate Time Series Regressor of different climatic features based on date and location, using Vector Auto-Regression (VAR) on Python and Visualization on R.

Jupyter Notebook

Flask-Image-Classifier

A simple server-side deployment of an Animal Image Classification Model using Flask.

Jupyter Notebook

Supermarket-Management

An efficient system for the management of the frontend and backend of a supermarket inventory, billing system and online shopping cart with strong searching, sorting, insertion, deletion and modification capabilities in a binary file database, developed using C++.

C++

Perceptron-Training-Algorithms

Python Code for Single-Layer Perceptron for the iris dataset and Multi-layer Perceptron trained for XOR, OR, AND and XAND truth tables.

Jupyter Notebook

Concept-Learning-Algorithms

Implementation of Find-S and Candidate Elimination Algorithms in Python. The find-S algorithm finds the most specific hypothesis that fits all the positive examples. The candidate elimination algorithm incrementally builds the version space given a hypothesis space and a set of examples.

Jupyter Notebook

Introduction-to-AI

Introduction to ML programming on Python during a three-week technical bootcamp in the track of Artificial Intelligence and Deep Learning, complete with assignments and learning modules.

Jupyter Notebook

DGA-Botnet-Detection

Analysis of the Domain Generation Algorithm and implementation of methodologies to detect DGA-based botnets using Deep Learning Approaches; comparison with traditional Machine Learning Classifiers.

Jupyter Notebook

NSE-Linear-Regressor

Multivariate Linear Regression Model for predicting different features of a particular share of Top Gainers in the NSE Equity Market. Dataset compiled and collected over a period of 2 weeks, in intervals of 5 minutes (weekdays, 09:15-15:15).

A simple login form that verifies password and username and has the functionality to detect too many attempts and lock the ability to login.

JavaScript

Updation-Form

A simple Employee Detail Update Form structure using MongoDB and NodeJS

JavaScript

Food-Image-Classifier

Convolution Neural Network for Food Image Classification

Jupyter Notebook

Classification-Algorithms

Implementation of Support Vector Machine (Linear & Non-Linear), k-Nearest Neighbour and Random Forest Algorithms for Classification on Python.

Jupyter Notebook

Decision-Tree-Classifier

A Decision Tree Classifier made from scratch (user-defined) for a sample dataset using information gain as node splitting criteria; functions for ID3 (Iterative Dichotomiser 3) algorithm and instance classification.

Jupyter Notebook

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