Machine Learning - End to End Data Science Projects
-
Updated
May 1, 2023 - Jupyter Notebook
Machine Learning - End to End Data Science Projects
This repository contains files for Udacity's Machine Learning Nanodegree Project: Boston House Price Prediction
Keras 101: A simple Neural Network for House Pricing regression
2018 [Julia v1.0] machine learning (linear regression & kernel-ridge regression) examples on the Boston housing dataset
All the essential resources and template code needed to understand major data science and machine learning libraries like Numpy, Pandas, Matplotlib and Scikit Learn with few small projects to demonstrate their practical application.
Implementation of 11 variants of Gradient Descent algorithm from scratch, applied to the Boston Housing Dataset.
Implement a perceptron from scratch
Predicting Boston House Prices
An Implementation of the Gradient Descent Algorithm on the 🏡Boston Housing DataSet🏡.
Boston Housing Prediction - 2nd project for Udacity's Machine Learning Nanodegree
Gradient Descent for N features using two datasets: Boston House data, Power Plant Data
Linear Regression , Cross Validation, k-mean clustering , Watershed , Gradients and Edge Detection , threshold , Correlation , Neural Network, Conventional Neural Network , Pneumonia Classification, Social Distancing, Rainfall Prediction, Boston Housing Price Prediction.
Dataset Boston Housing Price prediction
These are all the assignments from Udacity Nanodegree Machine Learning course
Machine Learning Nano-degree Project : To assist a real estate agent and his/her client with finding the best selling price for their home
Project #4 from the Cloud DevOps Engineer Nanodegree Program - Udacity
A project built as part of the udacity machine learning ND
Add a description, image, and links to the boston-housing-price-prediction topic page so that developers can more easily learn about it.
To associate your repository with the boston-housing-price-prediction topic, visit your repo's landing page and select "manage topics."