RsnLearning to Exploit Long-term Relational Dependencies in Knowledge Graphs, ICML 2019
Stars: ✭ 83 (-1.19%)
Neural Networksbrief introduction to Python for neural networks
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Fonduer TutorialsA collection of simple tutorials for using Fonduer
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Covid19 DataCOVID-19 workflows and datasets.
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CytokitMicroscopy Image Cytometry Toolkit
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PyeprPowerful, automated analysis and design of quantum microwave chips & devices [Energy-Participation Ratio and more]
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Deepembeding图像检索和向量搜索,similarity learning,compare deep metric and deep-hashing applying in image retrieval
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Mlcourse生命情報の機械学習入門(新学術領域「先進ゲノム支援」中級講習会資料)
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Kaggle QuoraKaggle Quora Questions Pairs Competition
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MlMachine learning projects, often on audio datasets
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Notebooks 📓 A growing collection of Jupyter Notebooks written in Python, OCaml and Julia for science examples, algorithms, visualizations etc
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GancsCompressed Sensing MRI based on Deep Generative Adversarial Network
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ArticlesPapers I read
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Airflow projectscaffold of Apache Airflow executing Docker containers
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Cs231nStanford cs231n'18 assignment
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LogomakerSoftware for the visualization of sequence-function relationships
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Spacenet building detectionProject to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.
Stars: ✭ 83 (-1.19%)
Chainer HandsonCAUTION: This is not maintained anymore. Visit https://github.com/chainer-community/chainer-colab-notebook/
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EconmlALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
Stars: ✭ 1,238 (+1373.81%)
Python script Manual《Python工具代码速查手册》是我们的python培训教材,主要面向数据分析方向。其中包含了python的常用总结性操作,使用jupyter notebook,利用markdown和script结果对常用操作进行总结,包括了使用方式和脚本。之所以使用notebook形式是可以方便大家编辑,方便大家形成自己的总结笔记。当然各位有更好的操作建议也欢迎向我们团队分享~
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Amazon Sagemaker Script ModeAmazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)
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Hops ExamplesExamples for Deep Learning/Feature Store/Spark/Flink/Hive/Kafka jobs and Jupyter notebooks on Hops
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CoronabrSérie histórica dos dados sobre COVID-19, a partir de informações do Ministério da Saúde
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Pulmonary Nodules SegmentationTianchi medical AI competition [Season 1]: Lung nodules image segmentation of U-Net. U-Net训练基于卷积神经网络的肺结节分割器
Stars: ✭ 84 (+0%)
ImageclassificationDeep Learning: Image classification, feature visualization and transfer learning with Keras
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PylbmNumerical simulations using flexible Lattice Boltzmann solvers
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Tensorflow DemoLocal AI demo and distributed AI demo using TensorFlow
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Esdastatistics and classes for exploratory spatial data analysis
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Unsupervised anomaly detectionA Notebook where I implement differents anomaly detection algorithms on a simple exemple. The goal was just to understand how the different algorithms works and their differents caracteristics.
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Nasnet KerasKeras implementation of NASNet-A
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TorchtexttutorialA short tutorial for Torchtext, the NLP-specific add-on for Pytorch.
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Nbconfluxnbconflux converts Jupyter Notebooks to Atlassian Confluence pages
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PancancerBuilding classifiers using cancer transcriptomes across 33 different cancer-types
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Yolo resnetImplementing YOLO using ResNet as the feature extraction network
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Carvana ChallengeMy repository for the Carvana Image Masking Challenge
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Dealing with dataMaterial that I use for a variety of classes and tutorials
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SeabornSeaborn 学习笔记
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FccssComputer Science SCHOOL resources
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Tensor LearningPython codes for low-rank tensor factorization, tensor completion, and tensor regression techniques.
Stars: ✭ 83 (-1.19%)