machine learning model deployment project of Iris classification model in a minimal UI using flask web framework and deployed it in Azure cloud using Azure app service

Overview

Machine Learning Model Deployment

Iris Classification

Hello everyone, this is a machine learning model deployment project where we have presented the Iris classification model in an elegant basic minimal ui using flask web framework and deployed it in Azure cloud using Azure app service. We initially made the notebook file, with model code and some data preperations (preprocessing). Then we have took some chunks of code and put the necessary in web project. Then we have deployed it into Azure app service. We initially made this project as a requirement for an internship at Indian Servers. We are now making it open to contribution.

Authors :

Tejaswi Talluru - Machine Learning Model.
Krishna Priyatham Potluri - flask web project and Azure deployment.

Step by step guide to run, contribute, test in local machine.

  1. clone this repo into desired location in your system using command: git clone https://github.com/kittupriyatham/Machine-Learning-Model-Deployment.git
  2. Go to the project folder using command: cd Machine-Learning-Model-Deployment
  3. Initialize local repository using command: git init
  4. create a python virtual environment using command: python -m venv venv
  5. activate the virtual environment using command: venv\Scripts\activate
  6. Install the project dependancies using command: pip install -r requirements.txt
  7. launch the flask server using command: flask run

Screenshots of deployed project

image

image

image

Steps to Deploy in Azure App Service

To be updated soon...

Apple-voice-recognition - Machine Learning

Apple-voice-recognition Machine Learning How does Siri work? Siri is based on large-scale Machine Learning systems that employ many aspects of data sc

Harshith VH 1 Oct 22, 2021
pandas, scikit-learn, xgboost and seaborn integration

pandas, scikit-learn and xgboost integration.

299 Dec 30, 2022
neurodsp is a collection of approaches for applying digital signal processing to neural time series

neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also inclu

NeuroDSP 224 Dec 02, 2022
This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning

This is a Cricket Score Predictor that predicts the first innings score of a T20 Cricket match using Machine Learning. It is a Web Application.

Developer Junaid 3 Aug 04, 2022
Probabilistic time series modeling in Python

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

Amazon Web Services - Labs 3.3k Jan 03, 2023
Generate music from midi files using BPE and markov model

Generate music from midi files using BPE and markov model

Aditya Khadilkar 37 Oct 24, 2022
Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Mert Sezer Ardal 1 Jan 31, 2022
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

MLJAR 2.4k Jan 02, 2023
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice

Responsible AI Workshop Responsible innovation is top of mind. As such, the tech industry as well as a growing number of organizations of all kinds in

Microsoft 9 Sep 14, 2022
Distributed deep learning on Hadoop and Spark clusters.

Note: we're lovingly marking this project as Archived since we're no longer supporting it. You are welcome to read the code and fork your own version

Yahoo 1.3k Dec 28, 2022
Predict the output which should give a fair idea about the chances of admission for a student for a particular university

Predict the output which should give a fair idea about the chances of admission for a student for a particular university.

ArvindSandhu 1 Jan 11, 2022
The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it inside a loop of Design, Model Development and Operations.

MLOps The MLOps is the process of continuous integration and continuous delivery of Machine Learning artifacts as a software product, keeping it insid

Maykon Schots 25 Nov 27, 2022
PySpark + Scikit-learn = Sparkit-learn

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Lensa 1.1k Jan 04, 2023
Python Machine Learning Jupyter Notebooks (ML website)

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

Tirthajyoti Sarkar 2.6k Jan 03, 2023
CobraML: Completely Customizable A python ML library designed to give the end user full control

CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us

Sriram Govindan 14 Dec 19, 2021
Predicting job salaries from ads - a Kaggle competition

Predicting job salaries from ads - a Kaggle competition

Zygmunt Zając 57 Oct 23, 2020
Simple Machine Learning Tool Kit

Getting started smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during data preparation testing your model The g

Alessandra Bilardi 1 Dec 30, 2021
Real-time stream processing for python

Streamz Streamz helps you build pipelines to manage continuous streams of data. It is simple to use in simple cases, but also supports complex pipelin

Python Streamz 1.1k Dec 28, 2022
Distributed Evolutionary Algorithms in Python

DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

Distributed Evolutionary Algorithms in Python 4.9k Jan 05, 2023
Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen.

SmartMeterEVN Dieses Projekt ermöglicht es den Smartmeter der EVN (Netz Niederösterreich) über die Kundenschnittstelle auszulesen. Smart Meter werden

greenMike 43 Dec 04, 2022