PCA vs Autoencoder

Comparison of classification algorithms in microarray data analysis

Supervised Machine learning - classification, regression, time-series forecast

This project can be widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine.

Now Classify Flower pictures with a Deep Learning Model. Model is trained from transfer learning using VGGnet.

This is an exercise to help understand Logistic Regression and also the interpretation of the model's coefficients!

This project aims to test my data manipulation, data visualization, and basic modelling skills to build linear regression and k-means clustering models.

Using Unsupervised Machine Learning to predict tradable cryptocurrencies for potential customer investments.

finding_donors machine learning model

This repository contains a comprehensive implementation of gradient descent for linear regression, including visualizations and comparisons with ordinary least squares (OLS) regression. It also includes an additional implementation for multiple linear regression using gradient descent.

Use various techniques to train and evaluate a model based on loan risk. Use a dataset of historical lending activity from a peer-to-peer lending services company to build a model that can identify the creditworthiness of borrowers.

This project is a California house price prediction system that utilizes machine learning techniques, specifically Linear Regression and Random Forest. The primary objective is to predict house prices in California based on various features such as location, number of bedrooms, population, and more. The project demonstrates how different regression

Image prediction model with logistic regression multiclass model, ML library as sklearn, Matplotlib using Python.

sap s/4 user support program

This Github repository contains projects related to KNN classification. Exploring Insights/Inferences by performing EDA on the given project data (Iphone purchase and Bangalore house price).

A SMS classifier is a machine learning model trained to categorize text messages, typically into spam or non-spam (ham) categories. This classification task involves processing large volumes of text data and extracting relevant features to distinguish between spam and legitimate messages.

Full stack Machine Learning based on kaggle dataset on Liver Patient lab report values

expression sequence machine learning application

A class of clustering methods that seek to build a hierarchy of clusters, in which some clusters contain others