Deep-neural-network Libraries

TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the…

If you prefer to use latest CNTK bits from master, use one of the CNTK nightly packages: You can learn more about using and contributing to CNTK with the following resources: Dear community, With our…

Input encrypted text, get the decrypted text back. "What type of encryption?" That's the point. You don't know, you just know it's possibly encrypted. Ciphey will figure it out for you. Ciphey can so…

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

To note a few features: The easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not address…

Extracting roads is challenging due to the occlusions caused by other objects and the complex traffic environment In instance segmentation, each individual 'instance' of a segmented area is given a u…

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

Then, define the BigDL model using Keras-style API:

If you use DLTK in your work please refer to this citation for the current version: Setup a virtual environment and activate it. Although DLTK<=0.2.1 supports and python 2.7, we will not support i…

BibTeX entry: Copyright 2018 the NiftyNet Consortium.

Python script for illustrating Convolutional Neural Networks (CNN). Inspired by the draw_convnet project [1]. python-pptx (if you want to save models as pptx) Keras (if you want to convert Keras sequ…

Deploy a quantized TensorFlowLite MobileNet V2 model on Android using the Arm NN SDK. Implement a neural style transfer on Android with Arm NN APIs. CMSIS project showing keyword spotting (KWS) and o…

This project presents a deep learning classifier able to predict the emotions of a human speaker encoded in an audio file. The classifier is trained using 2 different datasets, RAVDESS and TESS, and …

Note: These Self prepared Interview Questions will be updated weekly.

Here is how it looks in action: Get VergeML via pip: Verify your installation by typing: Let's create a very simple image classifier which tells apart cats from dogs. First, we create a new project f…

To classify videos into various classes using keras library with tensorflow as back-end. I have taken 5 classes from sports 1M dataset like unicycling, marshal arts, dog agility, jetsprint and clay p…

Extraction is a general term for methods of constructing combinations of the variables to get around these problems while still describing the data with sufficient accuracy Data visualization is the …

There are two options. Note: On each of those options, you'll find: No installations needed. Note: On each notebook, click on "Open in Colab", in order to open it on Google Colab Worried about whethe…

An experimental PyTorch implementation of Blind Image Quality Assessment Using A Deep Bilinear Convolutional Neural Network. Considering the popularity of PyTorch in academia, we hope this repo can h…

In this repo, we provide the Tensorflow and PyTorch implementations of our evaluation code for PieAPP v0.1 along with the trained models. We also provide a Win64 command-line executable. The input to…

Our augmentation method can accurately emulate realistic color constancy degradation. Existing color augmentation methods often generate unrealistic colors which rarely happen in reality (e.g., green…