Displaying 1 to 17 from 17 results

pytorch-tutorial - PyTorch Tutorial for Deep Learning Researchers

  •    Python

This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish Official Pytorch Tutorial.

YOLO_v3_tutorial_from_scratch - Accompanying code for Paperspace tutorial series "How to Implement YOLO v3 Object Detector from Scratch"

  •    Python

About when is the training code coming? I have my undergraduate thesis this May, and will be busy. So, you might have to wait for a till the second part of May.

PyTorch-Tutorial - Build your neural network easy and fast

  •    Jupyter

In these tutorials for pyTorch, we will build our first Neural Network and try to build some advanced Neural Network architectures developed recent years. Thanks for liufuyang's notebook files which is a great contribution to this tutorial.

Deep-Learning-Boot-Camp - A community run, 5-day PyTorch Deep Learning Bootcamp

  •    Jupyter

Tel-Aviv Deep Learning Bootcamp is an intensive (and free!) 5-day program intended to teach you all about deep learning. It is nonprofit focused on advancing data science education and fostering entrepreneurship. The Bootcamp is a prominent venue for graduate students, researchers, and data science professionals. It offers a chance to study the essential and innovative aspects of deep learning. Participation is via a donation to the A.L.S ASSOCIATION for promoting research of the Amyotrophic Lateral Sclerosis (ALS) disease.

Deep-Learning-Project-Template - A best practice for deep learning project template architecture.

  •    Python

A simple and well designed structure is essential for any Deep Learning project, so after a lot practice and contributing in pytorch projects here's a pytorch project template that combines simplicity, best practice for folder structure and good OOP design. The main idea is that there's much same stuff you do every time when you start your pytorch project, so wrapping all this shared stuff will help you to change just the core idea every time you start a new pytorch project. In order to decrease repeated stuff, we recommend to use a high-level library. You can write your own high-level library or you can just use some third-part libraries such as ignite, fastai, mmcv … etc. This can help you write compact but full-featured training loops in a few lines of code. Here we use ignite to train mnist as an example.

pytorch-beginner - pytorch tutorial for beginners

  •    Python

Toy project for pytorch beginner with simplest code.

Facial-Similarity-with-Siamese-Networks-in-Pytorch - Implementing Siamese networks with a contrastive loss for similarity learning

  •    Jupyter

The goal is to teach a siamese network to be able to distinguish pairs of images. This project uses pytorch. Any dataset can be used. Each class must be in its own folder. This is the same structure that PyTorch's own image folder dataset uses.

PyTorch-docset - PyTorch docset! use with Dash, Zeal, Velocity, or LovelyDocs.

  •    Python

Generate a docset for PyTorch documentation (0.2.0) and tutorials.

Deep-Image-Analogy-PyTorch - Visual Attribute Transfer through Deep Image Analogy in PyTorch!

  •    Jupyter

Unofficial,PyTorch version of Deep Image Analogy.https://arxiv.org/abs/1705.01088. This project focuses on documentation of the project , and simplifying the structure. A blog post on it is coming soon. This project uses Adam as optimizer instead of LBFGS. LBFGS was giving really poor results.

frontalization - Pytorch deep learning face frontalization model

  •    Python

Despite the apparent pessimism of the audience, thanks to machine learning today anyone with a little bit of Python knowledge and a large enough dataset can take a stab at writing a sci-fi drama worthy program. How to use NVIDIA's DALI library for highly optimized pre-processing of images on the GPU and feeding them into a deep learning model.

pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis

  •    Jupyter

This repo contains tutorials covering how to do sentiment analysis using PyTorch 0.4 and TorchText 0.2.3 using Python 3.6. The first 2 tutorials will cover getting started with the de facto approach to sentiment analysis: recurrent neural networks (RNNs). The third notebook covers the FastText model and the final covers a convolutional neural network (CNN) model.


  •    Java

The Android App uses Tensorflow-Mobile. You can find a prebuilt Sample APK in the release section.