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aaltd18

Data augmentation using synthetic data for time series classification with deep residual networks

ac_tpc

AC_TPC: Temporal Phenotyping using Deep Predicting Clustering of Disease Progression

bajiao01

初级试水

bajiao123

Config files for my GitHub profile.

baojiao

初级摸鱼

cancertypeprediction

This is the repository for paper titled as "Convolutional neural network models for cancer type prediction based on gene expression".

cnn-cardioprediction

Predicting cardiovascular heart disease using CNN

data-augmentation-for-tsc

Data augmentation using synthetic data for time series classification with deep residual networks

deep-belief-network

A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility

deep-learning-with-python-notebooks

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

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

ecg-tsc-fsl

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

ijcnn19ensemble

Deep Neural Network Ensembles for Time Series Classification

keras-io

Keras documentation, hosted live at keras.io

lstm-fcn

Codebase for the paper LSTM Fully Convolutional Networks for Time Series Classification

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

mimic-code

MIMIC Code Repository: Code shared by the research community for the MIMIC-III database

mimic3-benchmarks

Python suite to construct benchmark machine learning datasets from the MIMIC-III 💊 clinical database.

misc_examples

mixup-cifar10

mixup: Beyond Empirical Risk Minimization

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mlstm-fcn

Multivariate LSTM Fully Convolutional Networks for Time Series Classification

models

Models and examples built with TensorFlow

multilabel-timeseries-classification-with-lstm

Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

multivariate-time-series-forecasting-using-lstm

mytest

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

rnn

Using global optimisation searches to train recurrent neural network

scikit-survival

Survival analysis built on top of scikit-learn