In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

A best practice for tensorflow project template architecture.

tensorflow implementation of Grad-CAM (CNN visualization)

📖 👆🏻 Links Detector makes printed links clickable via your smartphone camera. No need to type a link in, just scan and click on it.

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications

Showing full TensorBoard support in Tensorflow for a CNN using MNIST data.

SEQ2SEQ model with Attention mechanism for QA also for NMT +(Generating text using LSTM network)

The fully connected neural network implemented in Numpy, from scratch, in Tensorflow and in Keras. The bonus code: Implementation of many different activation functions, in python, weight inits.

Pseudo Labelling on MNIST dataset in Tensorflow 2.x

Discord Bot in python with rasa nlu, tensorflow, discord api

머신러닝 프레임워크를 활용한 비교사(Unsupervised) 학습 모델 구현 프로젝트

Models, and associated helper code for GSOC 2017 project Tensorflow Image to Text in Apache Tika

Deep learning for image classification via transfer learning using Keras, PyTorch, and MXNet on Cloudera Data Science Workbench

A implement of pix2pix for tensorflow version(Image-to-Image Translation with Conditional Adversarial Nets)

Making mosaic art of a given image using tile images generated by a Stable Diffusion model using KerasCV

This repo dedicated to the project of Image processing and generating HTML file

In this Project we aim to dive into a Present Societal Pandemic issue which we are facing around us past 2 years due to outbreak of Novel Corona Virus.  Getting tested for covid-19 virus is not an easy deal with costly RT-PCR test, and delayed results, and with its no. of variants with different mutations emerging everyday all the new methods f…

Original Keras implementation of the code for the paper "Client-driven animated GIF generation framework using an acoustic feature," at 1171: Real-time 2D/3D Image Processing with Deep Learning (MTAP)