Fashion MNIST Classification
This is a web application for classifying images of clothing using various machine learning models. The models were trained on the Fashion MNIST dataset, which consists of 70,000 grayscale images of clothing items in 10 categories.

Usage
To use the application, simply upload an image of a clothing item and select a machine learning model from the dropdown menu. The application will then predict the category of clothing the image belongs to and display the predicted label along with the probabilities for each category.

Models
The following machine learning models are available in the application:

K-Nearest Neighbors
Decision Tree
Random Forest
AdaBoost
Gradient Boosting
The models were trained on the Fashion MNIST dataset using scikit-learn and saved as serialized files using pickle and joblib.

Dependencies
The application requires the following Python packages:

tensorflow
scikit-learn
joblib
pillow
gradio
You can install them using pip:

Copy code
pip install -r requirements.txt
Credits
This application was created by Praneeth Kandugula as a project for Saint Louis University . The machine learning models were trained on the Fashion MNIST dataset, which was created by Zalando Research. The web interface was built using Gradio.
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joblib region:us
TAGS
#joblib #region-us 

Fashion MNIST Classification
This is a web application for classifying images of clothing using various machine learning models. The models were trained on the Fashion MNIST dataset, which consists of 70,000 grayscale images of clothing items in 10 categories.

Usage
To use the application, simply upload an image of a clothing item and select a machine learning model from the dropdown menu. The application will then predict the category of clothing the image belongs to and display the predicted label along with the probabilities for each category.

Models
The following machine learning models are available in the application:

K-Nearest Neighbors
Decision Tree
Random Forest
AdaBoost
Gradient Boosting
The models were trained on the Fashion MNIST dataset using scikit-learn and saved as serialized files using pickle and joblib.

Dependencies
The application requires the following Python packages:

tensorflow
scikit-learn
joblib
pillow
gradio
You can install them using pip:

Copy code
pip install -r URL
Credits
This application was created by Praneeth Kandugula as a project for Saint Louis University . The machine learning models were trained on the Fashion MNIST dataset, which was created by Zalando Research. The web interface was built using Gradio.
TAGS
#joblib #region-us 

TAGS
#joblib #region-us 
