Posting My First Dev Post Notebook: Predicting house prices using LinearRegression
Excited to share my notebook which i made for experimenting with machine learning algorithms! This notebook contains code and markdown for a project using LinearRegression . It loads the dataset from load_boston dataset and enables us to predict house prices from the available actual houseprices ๐งโ๐ป๐
Concepts Used Include:
- Train_Test_Split๐
- LinearRegression ๐ฏ
- mean_squared_error โ
- model.coef_ ๐
- model.intercept_ ๐
- model.predict ๐
Why This Notebook:
The main goal of this notebook is to visually understand how to use the LinearRegression concept in machine learning algorithm to calculate/predict house prices from the training data we have.
Iโve included a line to my notebook to guide you through the it https://colab.research.google.com/drive/1-fGYNuGfMXjq172ErX7TWGoSPguU863f?usp=sharing
Whatโs Next:
Over the Next week, Iโll be posting more of my notebooks for other concepts in Machine Learning as recommended by this url https://www.kaggle.com/discussions/getting-started/554563 [# Machine Learning Engineer Roadmap for 2025]
Who's This For:
For anybody who loves python and who has been telling themselves I'm gonna learn Machine Learning one day. This is for them !Lets learn Machine Learning Together :)
Feel free to explore the notebook and try out your own machine learning models! ๐
Notebook Link: https://colab.research.google.com/drive/1-fGYNuGfMXjq172ErX7TWGoSPguU863f?usp=sharing [Project ML - Learn Linear Regression in Machine Learning through Python]
Kaggle References: https://www.kaggle.com/discussions/getting-started/554563 [Machine Learning Engineer Roadmap for 2025]
Top comments (2)
Hey there Iโm excited to learn Python this year especially ML/AI. Iโm ready to see what you have to share, and learn along with you. Not to mention the information you provided with those links to your notebook/kaggle were very great to read.
Thank you for those kind words :)
I'll start sharing my notebooks in future Dev Posts. And yes, lets learn along.