Image-Classification-using-Convolutional-Neural-Network-and-Logistic-Regression

Image Classification with Machine Learning Alogirthms deployed on Azure ML Studio

!Keyowrds: Azure Machine Learning Studio, Logistic regression, LeNet, AlexNet, Convolutional Neural Network, Pytorch, Python, hyperparameter tuning, Model Training and Deployment

The project is divided into five parts:

1. CIFAR-10 Dataset Overview
2. Model Implementation
3. Training Preparation
4. Model Training and Fine-tuning
5. Model Deploying

This Machine Learning end-to-end project consists of the following tasks:

1. Transform and normalize tensor data
2. Implement Logistic regression, LeNet, and AlexNet using PyTorch.
3. Perform hyperparameter tuning to meet a given performance requirement.
4. Identify the tradeoff between training time and training cost when using CPU vs GPU.
5. Deploy the trained model to a public API endpoint.

General Details The following table contains general information about this project module:

Prerequisites 	     :   Python3, PyTorch
Concepts 	     :   Deep Learning and Computer Vision, Machine Learning with Azure, PyTorch
Applicable languages :	 Python3
Applicable platform  :	 Jupyter Notebook, Azure Machine Learning Studio