gradio

Create UIs for your machine learning model in Python in 3 minutes

A sketch extractor for anime/illustration.

Creating a Gradio user interface to predict the sentiment of a tweet

Training & Implementation of chatbots leveraging GPT-like architecture with the aitextgen package to enable dynamic conversations.

EDA and Machine Learning Models in R and Python (Regression, Classification, Clustering, SVM, Decision Tree, Random Forest, Time-Series Analysis, Recommender System, XGBoost)

This project uses mammograms for breast cancer detection using deep learning techniques.

Landmark Detection (Google Lens like Interface) using TensorFlow Hub & Gradio

Example ML Project with a Hugging Face Space demo.

A 🔥 cookiecutter template for building Hugging Face Spaces

News articles summraizer with HuggingFace and Gradio App

A Space that builds a new space which compares multiple models from hugging face.

In this model we have tried to use ANN for image classification. We have learnt that ANN flattens the image pixels. This is why we loose some important information, and why ANN should not be preferred for image classification. How ever this project is solely based on the practicing and getting hands dirty and finding dis-advantages of an Architecture over another.

Just my take with Transfer Learning on Caltech101 dataset using ResNet-50 Convolutional Neural Network.

Churn predict interface with Random Forest, from: https://www.kaggle.com/blastchar/telco-customer-churn

This Python application is based on Hand Written Digits. Tensorflow and Gradio were used as the key requirements for coding. TensorFlow is a free and open-source software library for machine learning. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. Gradio allows you to quickly create customizable UI components around your TensorFlow or PyTorch models, or even arbitrary Python functions.

An app to apply filters to images to change the look and feel using opencv and convolution concepts.

Build a machine learning model that predicts the Envision Racing drivers’ lap times.

This is a repository used by Gradio in order to depploy my application for dog breeds classification.

App to segment FRF ARGUS c1 imagery

This project trains a machine learning model to recognize digits using Tensorflow Library and then it creates a web based GUI to show the Predictions from that model the predictions will be in real-time

Hand Written Digit-recognizer build with Tensorflow and Numpy. The interface for this module is built with Gradio.

Indian food classifier modelled after finetuning ResNet50 with PyTorch