Deploy DL/ ML inference pipelines with minimal extra code.

Distributed model cache for TF Serving

Creating a Dockerized stack environment using MLflow, mysql and Minio to manage the lifecycle of TensorFlow models.

This is an end-to-end project in the agricultural domain. A Convolutional Neural Network (CNN) model is trained to detect whether a tomato plant has a particular disease by using a picture of its leaf. The model can be accessed from a mobile application or a web page.

This is a deep learning project in agriculture domain that detect plants diseases

Simple examples of serving HuggingFace models with TensorFlow Serving

Serving YOLOv8 detection model with tf-serving

A minimalistic and pluggable machine learning platform for Kubernetes.

中文NER的那些事儿

A Flask REST API to serve trained ChatBots using Tensorflow Serving and Docker Containers

A React Native mobile application which is used to classify the potato disease by using convolutional neural networks and TensorFlow. This application also consists of ReactJs application which runs on the web, gives the classification results based on the image uploaded by the user.

This is the final project of the ML-Ops Dicoding class. This project serves to predict whether a person has lung cancer or not.

This is the first project of the ML-Ops Dicoding class. This project serves to classify whether a title is included in the clickbait category or not.

Brain Tumor Classification done by using deep-learning (CNN) for the sake of detecting and classifying different kinds of brain-tumors; for quick detection and providing correct medications. Link of the website 👇

Potato Disease Classification done by using deep-learning and for the sake of knowing various diseases caused to Potato plant and for quick remedial action. Link of the website 👇

finetune with keras

Bot for the online pokemon guessing game: https://gearoid.me/pokemon/

[Late Submission] Solution for Kuzushiji recognition (Kaggle competition)