CHAITHU1021

CHAITHU1021's Stars

• Mouneshgouda/Back-Office-Digitalization

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• Mouneshgouda/Insurance-claim

  Prediction of Auto Insurance Claim detection • Problem statement is related is to insurance domain • Performed a key role in Machine learning : Data gathering, cleaning ,Feature engineering ,Feature Selection ,Data visualization Model building ,Hyper parameter tunning • It’s a Classification problem evaluated model using confusion matrix and model

  Language:Jupyter Notebook25

• Mouneshgouda/Impact-of-Medication-for-Lifestyle-Diseases-on-Hospital-Readmission

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• Mouneshgouda/Data-Analysis-of-Job-Portal-in-machine-learning-in-Python

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• Mouneshgouda/Fashion-MNIST-SVM

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• Mouneshgouda/House_Rent

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• Mouneshgouda/fraud-detection-of-credit-card-

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• Mouneshgouda/Machine_Learning

  ChatGPT This repository features a diverse set of resources covering essential topics in machine learning and data analysis. From understanding and visualizing confusion matrices to exploring feature selection techniques and addressing multicollinearity, it offers comprehensive insights into model evaluation and feature engineering. Additionally

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• Mouneshgouda/Mouneshgouda

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• Mouneshgouda/MouneshGouda-

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• Mouneshgouda/Real-Time-Face-Emotion-Detection-Application

  "Real-Time-Face-Emotion-Detection-Application" is a publicly available project aimed at detecting facial expressions in real-time. Leveraging advanced computer vision techniques, it accurately identifies emotions such as happiness, sadness, anger, and surprise from live video feeds. With its intuitive interface,

  Language:Jupyter Notebook3813

• Mouneshgouda/Top-10-AI-Projects

  This repository curates a collection of the top 10 artificial intelligence projects from various domains. From cutting-edge research to practical applications, these projects showcase the latest advancements in AI technology.

  Language:Jupyter Notebook6047

• Mouneshgouda/Deep-learning

  This repository contains Jupyter Notebooks showcasing different techniques for price prediction using Artificial Neural Networks (ANNs). Topics covered include early stopping, batch normalization, dropout regularization, and deep neural networks. These notebooks offer practical implementations and insights for improving model training

  Language:Jupyter Notebook3611

• Mouneshgouda/Emotion-based-Music-Player-

  "Emotion-based-Music-Player" is a unique project designed to enhance music listening experiences. By analyzing user emotions, this player dynamically selects music tracks that match the user's mood. Through innovative algorithms, it tailors playlists to evoke desired emotional responses, offering a personalized journey through music.

  Language:Jupyter Notebook3510