dsc-jiit-128/Hacktoberfest_ML_Regression

This repository was created for people who are new to Open-source who can learn more and be an asset to the human society :octocat: This repository will help you understand the basics of Git, GitHub and hone you Machine Learning Skills!

HACKTOBERFEST 2020 is here! ✨

Boston House Pricing

SOURCE CODE ( GOOGLE COLAB )

• https://colab.research.google.com/drive/1lwY-Y4K7jAKbPFivsp5wrVZz-BTF3Udr?usp=sharing
• Provided as Hactoberfest_DSC_JIIT128_Regression.ipynb in the root directory.

TASK

• Create a Machine Learning Regression Model that can perform better on the Given Dataset

How to contribute

• Fork the repository and clone.
• Upload your notebook in .ipynb format inside Submissions folder.
• The file name should be of the format: <Your_Name>_<Your_College> For example: ManasDalakoti_JIIT128.ipynb
• Then add a Pull Request.

Important Notes

• Use the sklearn Boston House Pricing Dataset only.
• While doing test-train-split, use parameters test_size = 0.2 and random_state = 0.
• Advanced Deep Learning Algorithms can also be used.

How to reach us

• For additional information visit our Facebook page at

HURRAYYY!!! You just got closer to completing your Hacktoberfest challenge.🌱