Sample code from the Neural Networks from Scratch book.

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Deep Learningpythonmachine-learningdeep-learningpython3neural-networks
Overview

Neural Networks from Scratch (NNFS) book code

Code from the NNFS book (https://nnfs.io) separated by chapter. The NNFS book is written with the Python programming lanauge. If you're interested in seeing this same content, but with 40+ other programming languages, check out: https://github.com/sentdex/nnfsix

Owner
Harrison
Harrison
GitHub Repository https://nnfs.io
Source Code and data for my paper titled Linguistic Knowledge in Data Augmentation for Natural Language Processing: An Example on Chinese Question Matching

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YOLOX Win10 Project

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PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)

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Implementation of light baking system for ray tracing based on Activision's UberBake

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Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.

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Security evaluation module with onnx, pytorch, and SecML.

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Point Cloud Registration using Representative Overlapping Points.

Point Cloud Registration using Representative Overlapping Points (ROPNet) Abstract 3D point cloud registration is a fundamental task in robotics and c

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Object detection and instance segmentation toolkit based on PaddlePaddle.

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A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.

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Normalization Matters in Weakly Supervised Object Localization (ICCV 2021)

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Code for our paper Aspect Sentiment Quad Prediction as Paraphrase Generation in EMNLP 2021.

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Simple Python project using Opencv and datetime package to recognise faces and log attendance data in a csv file.

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In real-world applications of machine learning, reliable and safe systems must consider measures of performance beyond standard test set accuracy

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Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework

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Drone detection using YOLOv5

This drone detection system uses YOLOv5 which is a family of object detection architectures and we have trained the model on Drone Dataset. Overview I

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Implements pytorch code for the Accelerated SGD algorithm.

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Predicting path with preference based on user demonstration using Maximum Entropy Deep Inverse Reinforcement Learning in a continuous environment

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Pytorch implementation of "A simple neural network module for relational reasoning" (Relational Networks)

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