Web Application for Machine Learning Model Deployment

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. It focuses on the development of computer programs that can access data and use it learn for themselves.

About This Web App

Goal: Analysis of Machine learning model accuracy for a particular dataset on different ML algorithms.

• This project is about the deployment of any kind of machine learning/deep learning model over the internet.In machine learning we always face an issue of selecting the best Model for any dataset. For solving that problem, I have integrated many Ml Models on a single platform, so that we can compare the performance of different ML models for a specific dataset.

For this project, I am using Flask, HTML, CSS ,BootStrap and python for deploying the Model. *

Features

Multiple Kinds of Model Three kinds of model can be deployed on this website.

1. Regression Models
2. Classification Models
3. Deep Learning Models
4. Clustering Models

Regression Models

Linear Regression is a machine learning algorithm based on supervised learning. It performs a regression task. Regression models a target prediction value based on independent variables.

Classification Models

A classification model tries to draw some conclusion from the input values given for training. It will predict the class labels/categories for the new data.

Deep Learning Models

Deep learning is a class of machine learning techniques that exploit many layers of non-linear information processing for supervised or unsupervised feature extraction and transformation, for pattern analysis and classification.

Clustering Models

Clustering is a Machine Learning technique that involves the grouping of data points. Given a set of data points, we can use a clustering algorithm to classify each data point into a specific group.

Data Visualisation

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

Prediction

Requirements

1. Flask
2. HTML
3. CSS
4. Bootstrap
5. Python
6. Sklearn
7. numpy
8. pandas
9. matplotlib
10. Seaborn