aryan-sawant Goto Github PK

aryans

bharat_ml_01

Predicting House Prices: A linear regression model to estimate house prices using square footage of living room,lot ,basement and number of bedrooms, bathroom data.

bharat_ml_02

Explored wine quality prediction using Linear Regression .Crafting a model to assess wine quality based on various factors. 🍷📊

bharat_ml_03

Explore Iris Flowers Classification project with powerful classifiers: Logistic Regression, Decision Tree, Random Forest, k-Nearest Neighbors. Includes user input for real-time species classification. 🌺🤖

codsoft_1

The project classifies the movie genre with the help of movie plot in which I have used various concepts of NLP such as data cleanining,appropriate classifiers and appropriate feature extraction technique to get descent movie genre prediction.

codsoft_2

I have built a model to detect fraudulent credit card transactions by using various classification algorithms.

codsoft_3

I have built a model to predict customer churn based on their historical data,demographic data,behavior,gender,salary,etc; with the help of various classification algorithms.

codsoft_4

I have built a Spam SMS Detection model in which I have used various concepts of NLP such as data cleaning, appropriate classifiers and appropriate feature extraction technique.

cricketmanagementsystem

A Cricket Management System built using Python with the help of PyQT5 module and QT Designer, SQLite and VScode

deephandeqsolver

DeepHandEqSolver: A deep learning-based project for recognizing and solving handwritten mathematical expressions. Built with TensorFlow, Keras, and Streamlit, it offers a user-friendly GUI for real-time input and solution retrieval. Empowering efficient mathematical computation with advanced symbol recognition.

fithub-a-gym-website

🏋️‍♂️ FitHub: Your Ultimate Fitness Hub 🏋️‍♀️ Seamlessly blend gym management with exercise exploration! Admins manage members & staff, play music 🎶. Users explore diverse exercises, watch tutorials 📽️. Enjoy blogs, trainer profiles, posts, and future-ready Razorpay payments. Elevate your fitness journey!

fyghh

lgmvip--datascience-task-1

"Explore Iris Flowers Classification project with powerful classifiers: Logistic Regression, Decision Tree, Random Forest, k-Nearest Neighbors. Includes user input for real-time species classification. 🌺🤖

lgmvip--datascience-task-10

"Explore Moodsic: An AI project merging emotions and music. Using Facial Expression Recognition and CNNs, it suggests songs based on detected emotions. Challenges in aligning emotions and labels. A unique music experience! 🎵😊

lgmvip--datascience-task-3

Explore our Music Recommendation Model powered by Surprise library and SVD. Precise music suggestions & top 10 songs based on user preferences. 🎵🤖

lgmvip--datascience-task-4

Transformed Shri Krishna's image into a captivating pencil sketch using OpenCV. The artistic process included gray scaling, inverting, blurring, and inverting the blurred image. 📷✏️

lgmvip--datascience-task-5

Explore insights from global terrorism data through Exploratory Data Analysis (EDA). Utilized Matplotlib and Seaborn for visualizations. A valuable resource for security and defense analysts. 🌐📊

lgmvip--datascience-task-6

Explored Iris Flower Classification with Decision Trees, visualized the DT graph with Graphviz. Accurate species classification and insightful visualization. 🌺🌳

lgmvip--datascience-task-7

Explore Handwritten Digit Recognition using TensorFlow Keras with the MNIST dataset. Built a robust neural network model for accurate predictions. Added an interactive system for users to input unseen data. 📝🤖

lgmvip--datascience-task-8

Successfully built a Next Word Prediction Model with LSTM RNN, a significant achievement in my AI journey.📚🤖

lgmvip--datascience-task-9

Developed an efficient CNN model , achieving 99% validation accuracy. Recognizing digits and signs in handwritten equations, I built a function to solve them. Rigorous preprocessing and data augmentation contributed to this success.. 🚀📝

obisip-1

Explore Iris Flowers Classification project with powerful classifiers: Logistic Regression, Decision Tree, Random Forest, k-Nearest Neighbors. Includes user input for real-time species classification. 🌺🤖

obisip-2

Explore the nuances of unemployment trends with a data-driven model using Matplotlib, Seaborn, and Plotly Express. Gain insights into India's job market dynamics.📊📈

obisip-4

📱🚫 SMS Spam Detection with AI - Unmasking Unwanted Messages 🚀

obisip-5

Sales Price Prediction model that leverages Linear Regression to forecast sales based on TV, radio, and newspaper advertising expenditures. 📈💡

oibsip-3

Developed a predictive model for estimating used car prices using factors like present price, driven kilometers, fuel type, transmission, and used years. Explored regression models, with RandomForestRegressor showcasing optimal performance. 📊🚀

prodigy_ml_01

Predicting House Prices: A linear regression model to estimate house prices using square footage, bedroom, and bathroom data.

prodigy_ml_02

Use K-means clustering to group retail store customers based on their purchase history.

prodigy_ml_03

prodigy_ml_04

This repository showcases a highly accurate hand gesture recognition model, achieving up to 99.5% accuracy. The model identifies and classifies different hand gestures from image data, opening doors for intuitive human-computer interaction and gesture-based control systems.