Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Overview

Companion Jupyter notebooks for the book "Deep Learning with Python"

This repository contains Jupyter notebooks implementing the code samples found in the book Deep Learning with Python, 2nd Edition (Manning Publications).

For readability, these notebooks only contain runnable code blocks and section titles, and omit everything else in the book: text paragraphs, figures, and pseudocode. If you want to be able to follow what's going on, I recommend reading the notebooks side by side with your copy of the book.

These notebooks use Python 3.7 and Keras 2.0.8. They were generated on a p2.xlarge EC2 instance.

Table of contents

Owner
François Chollet
François Chollet
Vector Neurons: A General Framework for SO(3)-Equivariant Networks

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An energy estimator for eyeriss-like DNN hardware accelerator

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Build fully-functioning computer vision models with PyTorch

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Code release for NeX: Real-time View Synthesis with Neural Basis Expansion

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538 Jan 09, 2023
Bayesian optimisation library developped by Huawei Noah's Ark Library

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Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-art fuzzing techniques

About Fuzzification Fuzzification helps developers protect the released, binary-only software from attackers who are capable of applying state-of-the-

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[CVPR 2020] Interpreting the Latent Space of GANs for Semantic Face Editing

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GenForce: May Generative Force Be with You 1.3k Dec 29, 2022
Self-Supervised Image Denoising via Iterative Data Refinement

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A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK

Pytorch-MBNet A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK Training To train a new model, please ru

46 Dec 28, 2022
A torch.Tensor-like DataFrame library supporting multiple execution runtimes and Arrow as a common memory format

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Dynamic Capacity Networks using Tensorflow

Dynamic Capacity Networks using Tensorflow Dynamic Capacity Networks (DCN; http://arxiv.org/abs/1511.07838) implementation using Tensorflow. DCN reduc

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Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)

Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics

290 Dec 25, 2022
Experiments for Fake News explainability project

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Graph Attention Networks

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A Robust Non-IoU Alternative to Non-Maxima Suppression in Object Detection

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44 Sep 15, 2022
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The code for Bi-Mix: Bidirectional Mixing for Domain Adaptive Nighttime Semantic Segmentation

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Unofficial implement with paper SpeakerGAN: Speaker identification with conditional generative adversarial network

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Implementation for paper LadderNet: Multi-path networks based on U-Net for medical image segmentation

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