| ahkarami/Deep-Learning-in-Production |
4,138 |
|
0 |
0 |
over 2 years ago |
0 |
|
9 |
|
|
| In this repository, I will share some useful notes and references about deploying deep learning-based models in production. |
| imfing/keras-flask-deploy-webapp |
1,143 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
apache-2.0 |
JavaScript |
| :smiley_cat: Pretty & simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes. |
| merantix/picasso |
990 |
|
1 |
0 |
about 8 years ago |
5 |
May 15, 2017 |
18 |
epl-1.0 |
Python |
| :art: A CNN visualizer |
| matsui528/sis |
476 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
Python |
| Simple image search engine |
| kaushikjadhav01/Stock-Market-Prediction-Web-App-using-Machine-Learning-And-Sentiment-Analysis |
460 |
|
0 |
0 |
about 2 years ago |
0 |
|
21 |
mit |
Python |
| Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall |
| fchollet/hualos |
359 |
|
0 |
0 |
about 8 years ago |
0 |
|
14 |
mit |
Python |
| Keras Total Visualization project |
| jrosebr1/simple-keras-rest-api |
313 |
|
0 |
0 |
almost 7 years ago |
0 |
|
6 |
mit |
Python |
| A simple Keras REST API using Flask |
| machine-learning-apps/Issue-Label-Bot |
313 |
|
0 |
0 |
about 4 years ago |
0 |
|
2 |
mit |
SCSS |
| Code For The Issue Label Bot, an App that automatically labels issues using machine learning, available on the GitHub Marketplace. This is also code for the blog article: "How to automate tasks on GitHub with machine learning for fun and profit" |
| llSourcell/how_to_deploy_a_keras_model_to_production |
265 |
|
0 |
0 |
over 6 years ago |
0 |
|
12 |
gpl-3.0 |
Python |
| This is the code for the "How to Deploy a Keras Model to Production" by Siraj Raval on Youtube |
| bricewalker/Hey-Jetson |
189 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
gpl-3.0 |
Jupyter Notebook |
| Deep Learning based Automatic Speech Recognition with attention for the Nvidia Jetson. |
