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This project aims to develop a machine learning model to predict bike-sharing demand based on various factors such as weather conditions, time of day, and historical usage patterns. The dataset used for this project consists of 8760 records and 14 attributes.

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elasticnet-regression lasso-regression maachine-learning python ridge-regression adaboost decision-tree-regression gridsearchcv hyperparameter-tuning knn-regression

bike-sharing-demand-prediction's Introduction

Hi there 👋

I'm Preeti

With the heart of a data wizard and the brain of a number-crunching ninja, I'm ready to tackle any data puzzle that comes my way. Armed with the power of machine learning, computer vision, data visualization, and EDA, I can see patterns where others only see noise. I speak the language of Python, SQL, and statistics fluently and can translate complex data into actionable insights that drive business growth. So, let's join forces and unleash the full potential of data!

💻 Tech Stack:

Python Anaconda Flask MongoDB MySQL Keras NumPy Pandas Plotly PyTorch scikit-learn TensorFlow SciPy Docker

📊 GitHub Stats:



My Hobbies and interests:

  • Chess
  • Sketching
  • Painting
  • Volleyball
  • Travelling

🌐 Connect with me:

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