ImageclassificationDeep Learning: Image classification, feature visualization and transfer learning with Keras
Stars: ✭ 83 (+0%)
Yolo resnetImplementing YOLO using ResNet as the feature extraction network
Stars: ✭ 82 (-1.2%)
Sequence JacobianInteractive guide to Auclert, Bardóczy, Rognlie, and Straub (2019): "Using the Sequence-Space Jacobian to Solve and Estimate Heterogeneous-Agent Models".
Stars: ✭ 82 (-1.2%)
Spacenet building detectionProject to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.
Stars: ✭ 83 (+0%)
Openml RR package to interface with OpenML
Stars: ✭ 81 (-2.41%)
Nbconfluxnbconflux converts Jupyter Notebooks to Atlassian Confluence pages
Stars: ✭ 82 (-1.2%)
Amazon Sagemaker Script ModeAmazon SageMaker examples for prebuilt framework mode containers, a.k.a. Script Mode, and more (BYO containers and models etc.)
Stars: ✭ 82 (-1.2%)
Credit card fraudThis repository includes the code used in my corresponding Medium post.
Stars: ✭ 82 (-1.2%)
CoronabrSérie histórica dos dados sobre COVID-19, a partir de informações do Ministério da Saúde
Stars: ✭ 83 (+0%)
TorchtexttutorialA short tutorial for Torchtext, the NLP-specific add-on for Pytorch.
Stars: ✭ 83 (+0%)
Jupyter to mediumPython package for publishing Jupyter Notebooks as Medium blogposts
Stars: ✭ 82 (-1.2%)
Tensorflow DemoLocal AI demo and distributed AI demo using TensorFlow
Stars: ✭ 82 (-1.2%)
MapidocPublic repo for Materials API documentation
Stars: ✭ 81 (-2.41%)
Continuous analysisComputational reproducibility using Continuous Integration to produce verifiable end-to-end runs of scientific analysis.
Stars: ✭ 81 (-2.41%)
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.
Stars: ✭ 82 (-1.2%)
ArticlesPapers I read
Stars: ✭ 82 (-1.2%)
MadCode for "Online and Linear Time Attention by Enforcing Monotonic Alignments"
Stars: ✭ 81 (-2.41%)
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)
Stars: ✭ 83 (+0%)
Fonduer TutorialsA collection of simple tutorials for using Fonduer
Stars: ✭ 82 (-1.2%)
LogomakerSoftware for the visualization of sequence-function relationships
Stars: ✭ 83 (+0%)
Cs231nStanford cs231n'18 assignment
Stars: ✭ 82 (-1.2%)
RsnLearning to Exploit Long-term Relational Dependencies in Knowledge Graphs, ICML 2019
Stars: ✭ 83 (+0%)
GancsCompressed Sensing MRI based on Deep Generative Adversarial Network
Stars: ✭ 83 (+0%)
H3 Py NotebooksJupyter notebooks for h3-py, a hierarchical hexagonal geospatial indexing system
Stars: ✭ 82 (-1.2%)
DareblopyData Reading Blocks for Python
Stars: ✭ 82 (-1.2%)
GraphlogAPI for accessing the GraphLog dataset
Stars: ✭ 82 (-1.2%)
ErgoA Python library for integrating model-based and judgmental forecasting
Stars: ✭ 82 (-1.2%)
Deepembeding图像检索和向量搜索,similarity learning,compare deep metric and deep-hashing applying in image retrieval
Stars: ✭ 83 (+0%)
Juliaopt NotebooksA collection of IJulia notebooks related to optimization
Stars: ✭ 81 (-2.41%)
Neural Networksbrief introduction to Python for neural networks
Stars: ✭ 82 (-1.2%)
Dviz CourseData visualization course material
Stars: ✭ 81 (-2.41%)
Expo MfExposure Matrix Factorization: modeling user exposure in recommendation
Stars: ✭ 81 (-2.41%)
Video2gif codeVideo2GIF neural network model from our paper at CVPR2016
Stars: ✭ 80 (-3.61%)
PyeprPowerful, automated analysis and design of quantum microwave chips & devices [Energy-Participation Ratio and more]
Stars: ✭ 81 (-2.41%)
PylbmNumerical simulations using flexible Lattice Boltzmann solvers
Stars: ✭ 83 (+0%)
Esdastatistics and classes for exploratory spatial data analysis
Stars: ✭ 83 (+0%)
Carvana ChallengeMy repository for the Carvana Image Masking Challenge
Stars: ✭ 83 (+0%)
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 (+1391.57%)
Nasnet KerasKeras implementation of NASNet-A
Stars: ✭ 82 (-1.2%)