Skip to content
#

gradientboostingregressor

Here are 19 public repositories matching this topic...

This repo hosts an end-to-end machine learning project designed to cover the full lifecycle of a data science initiative. The project encompasses a comprehensive approach including data Ingestion, preprocessing, exploratory data analysis (EDA), feature engineering, model training and evaluation, hyperparameter tuning, and cloud deployment.

  • Updated Feb 28, 2024
  • Jupyter Notebook

This project aims to analyze and forecast the total funding amounts of startups using various regression and time series modeling techniques. Initially, we preprocess the dataset, which includes features such as funding amounts, company size, and number of funding rounds. The data is then scaled and split into training and testing sets.

  • Updated Aug 19, 2024
  • Jupyter Notebook

This research is based on previous research related to Optimization of Airbnb Dynamic Pricing. This research analytical purposes was to create a model that was as flexible as possible by determining price at the scale of the smallest possible rental period at daily basis.

  • Updated Nov 27, 2022
  • Jupyter Notebook

Sales forecasting plays an important role in business development. Regardless of the size of a business or the number of salespeople, accurate sales forecasting can have a significant impact on all aspects of sales management, including planning, budgeting, and determining sales.

  • Updated Aug 14, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the gradientboostingregressor topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the gradientboostingregressor topic, visit your repo's landing page and select "manage topics."

Learn more