AtulJoshi1's Stars
MaartenGr/BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
Techcatchers/PyLyrics-Extractor
Get Lyrics for any songs by just passing in the song name (spelled or misspelled) in less than 2 seconds using this awesome Python Library.
Oprishri/Supply-Chain-Analytics-Project
Demand forecasting of items using three step machine learning model. Clustering - Classification - Prediction
abhashpanwar/autoscraper
autoscraper
anurag0308/Covid-19-worldwide-evolution
Dash 🚀 with animated scatter map on mapbox/plotly (COVID data) for tracking day to day evolution of COVID-19 through the world.
Pawan300/Hadoop-practical-
anurag0308/Predicting-Household-energy-consumption-using-LSTM
anurag0308/Time-Series
Code done as part of my course-work.
Pawan300/hackathons
Pawan300/twitter-data-preprocessing
Pawan300/HUSE-hierarchical-universal-semantic-embeddings-
Pawan300/NLP
Pawan300/Simple-chatbot
anurag0308/Dimensionality-Reduction
This includes dimensionality reduction techniques like PCA & SVD.
abhichand26/google-images-scrap
A python script to scrap google images using Selenium
abhish-one/Market-Structure-Analysis
This repository contains code for Clustering analysis and Correspondence analysis of online user reviews of Digital Camera . The reviews were collected using web scraping .
anurag0308/Data-Mining
anurag0308/HRanalytics
AnalyticsVidhya HR analytics problem
anurag0308/Natural_Languange_Processing
anurag0308/Predicitng-Success-of-Bank-telelmarketing-calls-
anurag0308/RandomWalks
Includes code of PageRank algorithm and Modified Version of PageRank Algorithm
anurag0308/Regression
Regression Techniques like Linear Regression, Logistic Regression, Lasso , Ridge implemented from scratch
anurag0308/Email_reply_prediciton
Problem Statement: To predict whether a given mail will get a reply or not. Given Dataset: A text file with emails and their metadata in hierarchy To predict: Reply/ No reply Our Approach: Load Data Extracting Data: Extracting text email subject and body data from the text file Text Data Cleaning and Preprocessing Feature engineering : extracting additional features from emails (such as header subject length, email body lengths, recepient count, attachment count) Modelling: 5.1 BERT Embeddings from the text data 5.2 combine with other features 5.3 train test split 5.4 predict using MLP classifier 5.5 check F-1 score and plot ROC
anurag0308/RandomGraphs
Code Demonstrating Phase Chnages in RandomGraphs
Pawan300/Javascript_projects
This is me learning Javascript.
Pawan300/Power-BI-work
This dashboards I tried in Power BI.
AtulJoshi1/Predicting-Success-of-Bank-Telemarketing-Calls
Predicting success of Bank Telemarketing Calls: Implementing and Comparing various ML classification algorithms
Pawan300/Deep-learning-projects
shikharkumar13/Heart-Disease-Classification