Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data
-
Updated
Dec 18, 2018 - Python
Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data
<개발자를 위한 머신러닝&딥러닝> 도서의 코드 저장소
Here's the code associated with my Machine Learning (ML) based hurricane forecasting system
Example to load, train, and evaluate ImageNet2012 dataset on a Keras model
Code relevant for training, evaluating, assessing, and deploying CNNs for image classification and segmentation of Digital Mammography images
An image augmentation library for tensorflow. It can be used seamlessly with tf.data.Dataset
TinyML project. This system monitors your room or surrounding with an onboard microphone of Arduino nano BLE sense. Still Under Developement
Multi-task classification project, with the custom training loop implemented from scratch in TF 2.2+ and the usage of "tf.data.Dataset" object for handling the data.
Convolutional Denoising Autoencoder for low light image denoising
Computer Vision project, built around Convolutional neural network (CNN) for multi-class classification. The project represents an attempt to build modular, OOP approach with an example of how to use modules on MNIST 10-class classification.
A web app designed for identifying different disseases for a specific crop
A library to help with the development of AI models with Keras, with a focus on edge / IoT applications. Based originally on https://github.com/yingkaisha/keras-unet-collection
A simple implementation AlexNet
German Traffic Signs Classification
Streamlit Demo of CIFAR10 Data Classifiers
Add a description, image, and links to the tf-data topic page so that developers can more easily learn about it.
To associate your repository with the tf-data topic, visit your repo's landing page and select "manage topics."