Proyek pertama predictive analytics untuk membangun model machine learning yang dapat memprediksi harga sewa rumah dan apartement di India.
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Updated
Sep 18, 2022 - Jupyter Notebook
Proyek pertama predictive analytics untuk membangun model machine learning yang dapat memprediksi harga sewa rumah dan apartement di India.
A collection of machine learning models for predicting laptop prices
Food Delivery Time Prediction using Machine Learning
This project uses machine learning to predict the price of a used car. The model is trained on a dataset of historical car sales data, and it can then be used to predict the price of a car based on its features.
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.
Predicting cement strength
This mini-project involves experimenting with a variety of classification and regression models, exploring different techniques to understand their behaviors and applications in predictive analytics.
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.
Developed student performance predicting model, showing strong understanding of predictive modeling techniques.
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.
Predicting Compressive Strength of Concrete
The purpose of this notebook is to develop an automated function to predict the price of a diamond based on its given features (cut, color, dimensions, etc.). We will create a machine learning model which can estimate these values. We need to find continuous data, so we will perform a regression task. We will use supervised learning to find the …
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