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AI / ML
AI / ML
Linear Regression Model
Predictive Data Analysis with Machine Learning
A machine learning model developed during the YBI Foundation internship to predict numerical values based on historical data trends.
The project involves an end-to-end ML workflow, from data cleaning and preprocessing to implementing a Linear Regression algorithm for regression tasks.
Developed and tested within the Google Colab environment, the model utilizes industry-standard Python libraries to analyze and visualize predictive performance.
Technologies Used
Pythonscikit-learnPandasMatplotlibGoogle ColabJupyter Notebook
What I Learned
- ▹Practical implementation of Linear Regression for numerical prediction
- ▹Data preprocessing and feature handling using Pandas
- ▹Visualizing model performance and data trends with Matplotlib
- ▹Managing collaborative ML projects in Google Colab
- ▹Evaluating model accuracy and error metrics
Unique Aspects
✦Real-world data trend prediction and analysis
✦Detailed visual regression performance mapping
✦Optimized for high readability in Jupyter/Colab formats
✦Internship-certified industry standard practices