Shreya Patil's repositories
Magic_Telescope_Classification
Welcome to the MAGIC Gamma Telescope project! 🌌 The mission is to classify gamma rays and hadrons in astrophysics using machine learning techniques like Logistic Regression, Decision Tree, Random Forest, and Ensemble. Unraveling the universe's mysteries! 🚀 #Astrophysics #MachineLearning
50_Startups_Profit
This dataset contains four independent variables: R&D Spend, Administration, Marketing Spend, and State. Our task is to use this data to train a Machine Learning model that can understand how these variables relate to the Profit. With this knowledge, we can predict the profit for a new company based on its data.
Aircraft_Damage_Prediction
The objective of the project on Aviation Accident Damage from the National Transportation Safety Board (NTSB) is to thoroughly investigate and analyze aviation accidents in order to understand the causes and consequences of these incidents.
Big_Mart_Sales_Prediction
Big Mart Sales Prediction is a data-driven project aiming to forecast product sales accurately across Big Mart outlets. Leveraging machine learning and comprehensive datasets, our project empowers retailers to optimize inventory, enhance profitability, and make informed decisions in the dynamic world of retail.
CLUSTERING_COUNTRIES
Dedicated to HELP International's 🌍 mission of alleviating poverty, this GitHub repository offers a Python-based project. It clusters countries by vital socio-economic factors, ensuring efficient resource allocation. Commencing with data inspection and cleaning, it identifies countries needing aid through a comprehensive analysis.
Data_Science_Salary_Prediction
The objective of the project is to conduct a comprehensive analysis of a dataset of data science job postings, identifying the most important factors that influence salaries. Build predictive models that can be used to predict salaries for data science professionals, taking into account factors such as experience level, education, skills etc.
Enzyme_Substrate_Classification
The objective of this classification project is to build predictive models using machine learning algorithms to map the relationships between enzymes and their possible substrates. The project will involve data preprocessing, feature engineering, model training, hyperparameter tuning, and performance evaluation to achieve the most efficient result
Gender_By_Name
This dataset compiles the number of occurrences of male and female baby names during specific time periods. It then calculates the probability of a name based on the total count. The data comes directly from government authorities, ensuring its credibility.
Glass_Indentification
This repository contains a machine-learning project that focuses on classifying different types of glass based on their chemical properties. The dataset comprises various features, including refractive index, percentage of elements like sodium, magnesium, aluminium, silicon, potassium, calcium, barium, and iron, as well as the type of glass.
Laptop-Price-Predictor
Predict laptop prices using machine learning. This project leverages multiple linear regression to achieve an 82% prediction precision. Explore the influence of features like brand, specs, and more on laptop prices.
Life_Expectancy
The overall objective of this project is to critically analyze and develop the relationships of quantitative factors affecting life expectancy in 193 countries between 2000 and 2015 that underlie changes in life expectancy. The importance of predicting life expectancy arises because of its important role as an indicator of the overall health.