Setting up a Jupyterhub Dockercontainer to spawn Jupyter Notebooks with GPU support (containing Tensorflow, Pytorch and Keras)
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Aug 21, 2019 - CSS
Keras is an open source, cross platform, and user friendly neural network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, R, Theano, and PlaidML.
Setting up a Jupyterhub Dockercontainer to spawn Jupyter Notebooks with GPU support (containing Tensorflow, Pytorch and Keras)
GUI for Keras and TensorFlow with integrated hyperparameter optimization and NLP
This project aims to classify various types of dog skin diseases using deep learning models with images.
Automatically restore Romanian diacritics from flat text using neural nets
license plate recognition system will work with camera to identify the plate number of the car that tries to enter the parking lot, and also check if the car allowed/not allowed to enter by checking the DB of the system.
{data scribers} is a collection of posts about data science. And unlike other content aggregating sites, this one encourages people to visit the blog's actual site.
SANUS - A CADx Platform. To detect diseases with medical records.
Python web based application built with the Django framework. Contains several tools from PIL and Deep Learning with Keras.
An application working as assistant a doctor
Handwritten Digits Classifier: An Online AI Classifier Trained With the MNIST Dataset...
Check wound severity and your medical history recorder.
Creates a Convolutional Neural Net that recognizes the genre of music by analyzing slices of a song's spectrogram
Pagina Web para un Modelo IA
This project applies predictive analytics to forecast stock market movements using machine learning on historical prices, trading volumes, and macroeconomic data. It tests models like time series, regression, and ensemble methods to predict prices. The goal is to provide a tool for data-driven investment decisions.
A simple flask app for detecting covid-19 from chest x-ray images.
A CADx Platform
Time series prediction system for a Zvijezda d.d. warehouse, part of the Inovativko competition held by mStart
Created by François Chollet
Released March 27, 2015