Python implementaion of missing value imputation using K-Nearest-Neighbour and Weighted K-Nearest-Neighbour
-
Updated
Dec 25, 2019 - Python
Python implementaion of missing value imputation using K-Nearest-Neighbour and Weighted K-Nearest-Neighbour
In this project, the selling price of the houses have been predicted using various Regressors, and comparison charts have been shown that depict the performance of each model. This submission was ranked 107 out of 45651 in first attempt on Kaggle leader-board which can be accessed from here : https://www.kaggle.com/c/home-data-for-ml-course/lead…
This contains the Jupyter Notebook and the Dataset for the mentioned Classification Predictive Modeling Project
Predictive Analytics
Fictional investment bank, Accountability Accounting, is interested in offering a new cryptocurrency investment portfolio to its clients; however, the company needs assistance in determining which cryptocurrencies they should offer and would like them grouped to create a classification system for this new investment. A clustering algorithm was u…
In this Classification Machine Learning Project, we will be analysing the dataset taken from www.kaggle.com related to details of credit card owners. This data consists of features like Gender, Income type, House type, marital status and many more. Our focus will be on analysing the data, getting the insights related to these features and there …
This project helps the patient to find the best doctor in that area or may be used for finding a better doctor for a second opinion.ML model to work on with data set of doctors profile and based on this we will ask the user to input certain data fields to predict the best/better doctor in that location (if any).
Big Data Project - SSML - Spark Streaming for Machine Learning
A machine learning model that attempts to predict whether a loan will become high risk or not
To model the demand for shared bikes with the available independent variables
A guided project provided by datacamp.
A machine learning exercise using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.
A Spotify Hit Predictor capable of predicting whether any given track would be a 'Hit' or 'Flop'. By using the Spotify "hit predictor" dataset, with data analysis of past "hits" by decade. Deployment using Flask via Heroku.
Linear Multilinear and Logistic Regression in Machine Learning
Add a description, image, and links to the minmaxscalar topic page so that developers can more easily learn about it.
To associate your repository with the minmaxscalar topic, visit your repo's landing page and select "manage topics."