basic tutorial on pytorch

Overview

Quick Tutorial on PyTorch

  1. PyTorch Basics
  2. Linear Regression
  3. Logistic Regression
  4. Artificial Neural Networks
  5. Convolutional Neural Networks
  6. Recurrent Neural Networks
  7. LSTM
  8. GPU

Dataset

The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning.

The MNIST database contains 60,000 training images and 10,000 testing images.

alt text

The CIFAR-10 dataset is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. The 10 different classes represent airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks. There are 6,000 images of each class

alt text

Contents

To Do:

  • CNN
  • RNNN
  • LSTM
  • GPU
Owner
Interested in artificial intelligence, machine learning and deep learning besides electronics.
A collection of models for image<->text generation in ACM MM 2021.

Bi-directional Image and Text Generation UMT-BITG (image & text generator) Unifying Multimodal Transformer for Bi-directional Image and Text Generatio

Multimedia Research 63 Oct 30, 2022
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

Alibaba 21 Dec 21, 2022
A Deep Learning Framework for Neural Derivative Hedging

NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa

GUIJIN SON 17 Nov 14, 2022
A modular domain adaptation library written in PyTorch.

A modular domain adaptation library written in PyTorch.

Kevin Musgrave 225 Dec 29, 2022
When are Iterative GPs Numerically Accurate?

When are Iterative GPs Numerically Accurate? This is a code repository for the paper "When are Iterative GPs Numerically Accurate?" by Wesley Maddox,

Wesley Maddox 1 Jan 06, 2022
Self-Adaptable Point Processes with Nonparametric Time Decays

NPPDecay This is our implementation for the paper Self-Adaptable Point Processes with Nonparametric Time Decays, by Zhimeng Pan, Zheng Wang, Jeff M. P

zpan 2 Sep 24, 2022
TAP: Text-Aware Pre-training for Text-VQA and Text-Caption, CVPR 2021 (Oral)

TAP: Text-Aware Pre-training TAP: Text-Aware Pre-training for Text-VQA and Text-Caption by Zhengyuan Yang, Yijuan Lu, Jianfeng Wang, Xi Yin, Dinei Flo

Microsoft 61 Nov 14, 2022
Real-CUGAN - Real Cascade U-Nets for Anime Image Super Resolution

Real Cascade U-Nets for Anime Image Super Resolution 中文 | English 🔥 Real-CUGAN

tarsin 111 Dec 28, 2022
A TensorFlow implementation of DeepMind's WaveNet paper

A TensorFlow implementation of DeepMind's WaveNet paper This is a TensorFlow implementation of the WaveNet generative neural network architecture for

Igor Babuschkin 5.3k Dec 28, 2022
Supplementary materials to "Spin-optomechanical quantum interface enabled by an ultrasmall mechanical and optical mode volume cavity" by H. Raniwala, S. Krastanov, M. Eichenfield, and D. R. Englund, 2022

Supplementary materials to "Spin-optomechanical quantum interface enabled by an ultrasmall mechanical and optical mode volume cavity" by H. Raniwala,

Stefan Krastanov 1 Jan 17, 2022
HuSpaCy: industrial-strength Hungarian natural language processing

HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti

HuSpaCy 120 Dec 14, 2022
This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian

Aryclenio Xavier Barros 26 Oct 14, 2022
【CVPR 2021, Variational Inference Framework, PyTorch】 From Rain Generation to Rain Removal

From Rain Generation to Rain Removal (CVPR2021) Hong Wang, Zongsheng Yue, Qi Xie, Qian Zhao, Yefeng Zheng, and Deyu Meng [PDF&&Supplementary Material]

Hong Wang 48 Nov 23, 2022
Efficient Multi Collection Style Transfer Using GAN

Proposed a new model that can make style transfer from single style image, and allow to transfer into multiple different styles in a single model.

Zhaozheng Shen 2 Jan 15, 2022
RSNA Intracranial Hemorrhage Detection with python

RSNA Intracranial Hemorrhage Detection This is the source code for the first place solution to the RSNA2019 Intracranial Hemorrhage Detection Challeng

24 Nov 30, 2022
PyTorch implementation of "Learning to Discover Cross-Domain Relations with Generative Adversarial Networks"

DiscoGAN in PyTorch PyTorch implementation of Learning to Discover Cross-Domain Relations with Generative Adversarial Networks. * All samples in READM

Taehoon Kim 1k Jan 04, 2023
[MICCAI'20] AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

AlignShift NEW: Code for our new MICCAI'21 paper "Asymmetric 3D Context Fusion for Universal Lesion Detection" will also be pushed to this repository

Medical 3D Vision 42 Jan 06, 2023
KinectFusion implemented in Python with PyTorch

KinectFusion implemented in Python with PyTorch This is a lightweight Python implementation of KinectFusion. All the core functions (TSDF volume, fram

Jingwen Wang 80 Jan 03, 2023
This is the pytorch code for the paper Curious Representation Learning for Embodied Intelligence.

Curious Representation Learning for Embodied Intelligence This is the pytorch code for the paper Curious Representation Learning for Embodied Intellig

19 Oct 19, 2022
Implementation of the GVP-Transformer, which was used in the paper "Learning inverse folding from millions of predicted structures" for de novo protein design alongside Alphafold2

GVP Transformer (wip) Implementation of the GVP-Transformer, which was used in the paper Learning inverse folding from millions of predicted structure

Phil Wang 19 May 06, 2022