yuhjyhlin Goto Github PK

ae-cnn

(ICVGIP' 18 Oral Paper) Classification of thoracic diseases on ChestX-Ray14 dataset

apm_exercises

Exercises for the book Applied Predictive Modeling by Kuhn and Johnson (2013)

arraytools

Misc information for BRB-ArrayTools users

autokeras

An AutoML system based on Keras

awesome-feature-engineering

A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning

biodiscml

Large-scale automatic feature selection for biomarker discovery in high-dimensional OMICs data

building-ml-and-dl-models-on-gcp

Source code for 'Building Machine Learning and Deep Learning Models on Google Cloud Platform'

c9-python-getting-started

Sample code for Channel 9 Python for Beginners course

chexnet-keras

This project is a tool to build CheXNet-like models, written in Keras.

chexnet-mxnet

A mxnet implementation of CheXNet

chexnet-with-localization

Weakly Supervised Learning for Findings Detection in Medical Images

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks.

detrac_covid19

diseasesdetection-on-chestxrays-with-deeplearning

CS541-Deep Learning Course Project

feature-engineering-and-feature-selection

A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.

gbtm

gbtm counter

gwa_tutorial

A comprehensive tutorial about GWAS and PRS

hands-on-scikit-learn-for-mach-learning-apps

Source code for 'Hands-on Scikit-Learn for Machine Learning Applications' by David Paper

hs-i-

R Programming and its applications in Management Science(R 語言 在管理領域的應用)

innvestigate

A toolbox to iNNvestigate neural networks' predictions!

ipython-in-depth

IPython and Jupyter in-depth Tutorial, first presented at PyCon 2012

keras-rcnn

Keras package for region-based convolutional neural networks (RCNNs)

keras-yolov4

supports training, at least 41.1% mAP.支持训练，至少41.1%mAP。少数的给出精度的复现。

keras_medicalimgai

lime

Lime: Explaining the predictions of any machine learning classifier

logistic_regression_demo

lrp_toolbox

The LRP Toolbox provides simple and accessible stand-alone implementations of LRP for artificial neural networks supporting Matlab and Python. The Toolbox realizes LRP functionality for the Caffe Deep Learning Framework as an extension of Caffe source code published in 10/2015.

mastering-machine-learning-with-scikit-learn-second-edition

Mastering Machine Learning with scikit learn Second Edition, published by Packt

mimic-code

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

napari-training-course

Lectures for a napari training course