Build your neural network easy and fast
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Updated
Jun 8, 2020 - Jupyter Notebook
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Build your neural network easy and fast
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
Tensorflow tutorial from basic to hard
This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.
[CVPR2020] Adversarial Latent Autoencoders
텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다
[unmaintained] An open-source convolutional neural networks platform for research in medical image analysis and image-guided therapy
Use unsupervised and supervised learning to predict stocks
Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
Advanced Deep Learning with Keras, published by Packt
TensorFlow and Deep Learning Tutorials
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Next RecSys Library
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
DanceNet -
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Tensorflow implementation of variational auto-encoder for MNIST
Torch implementations of various types of autoencoders
Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.
Autoencoder for Point Clouds
도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Representation learning for link prediction within social networks
A curated list of dedicated resources and applications
Tensorflow implementation of Adversarial Autoencoders
A Variational Autoencoder (VAE) implemented in PyTorch
中文的 tensorflow tutorial with jupyter notebooks
Learning deep representations by mutual information estimation and maximization
Image reconstruction done with untrained neural networks.
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I'm using latest pyod version on pypi. How to generate simulated data where x-axis is time? Thank you.