A final project in Sharing Vision Data Science Bootcamp
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Updated
Mar 27, 2023 - Jupyter Notebook
A final project in Sharing Vision Data Science Bootcamp
Creating a Machine Learning model to predict the home prices.
In this project, the objective was to predict house prices in 6 metropolitan cities of India. The dataset provided contained essential features and amenities of houses in these cities. To achieve accurate predictions, a systematic approach was followed, encompassing exploratory data analysis, feature engineering and model building.
House Price Prediction using different regression models like Linear, Ridge, Lasso, Elastic Net, Random Forest, XGBoost, K-Nearest Neighbours, Support Vector Regressor, XGBoost. Also, multi-layer perceptron(MLP) was implemented using TensorFlow
Revolutionize sales forecasting for Rossmann stores with our high-accuracy XGBoost model, leveraging data analysis, feature engineering, and machine learning to predict sales up to six weeks in advance.
By applying data preprocessing, exploratory data analysis, feature selection, model training, and evaluation techniques, develop a predictive model that can accurately predict the survival status of passengers aboard the Titanic.
Prediction of Crop Cultivation using Machine Learning
Predicting the Gender of the riders of New York Citi Bikes (2015-2017)
R library to create high quality NLP-based features from FROG output
A Comprehensive Guide to Titanic Machine Learning from Disaster
I worked on Breast Cancer Wisconsin (Diagnostic) Data Set and I made predict with Sci-Kit Learn library.
Machine Learning modelling for a classification problem.
Notebooks in this repository focus on code related to machine learning topics
Predicting whether the loan will default using a classification algorithm in Python
Consolidating Brazilian exports/imports by Mesoregions
Kaggle's NCAA® ML Competition March Madness Competition presents a challenge to forecast the outcomes of all possible matchups in the Men’s and Women's Basketball Championships.
Diet-planner for Seniors
This is a project based on the FIFA World Cup 2019 and Analyzes the Performance and Efficiency of Teams, Players, Countries and other related things using Data Analysis and Data Visualizations
Develop a predictive model to understand the LTV of each customer for a DTC meal-kit business.
Predicts salary based on job descriptions
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