keshava Goto Github PK

energy-transitions-lab

energy-transitions-sb-ctl

Energy Transitions Sandbox Control

engine

Open Source Risk Engine

enm360

enterprise-scale

The Enterprise Scale architecture provides prescriptive guidance coupled with Azure best practices.

ep

Distributed Query Processing & Execution Framework

esc-50

ESC-50: Dataset for Environmental Sound Classification

eshoponcontainersai

eShopOnContainers with AI, ML and Bots features

ethereumbook

Mastering Ethereum, by Andreas M. Antonopoulos, Gavin Wood

etp.net

Energistics Transfer Protocol message serialization library for .NET.

eventmesh

The cloud native event-driven runtime

excelnumericaldemos

A set of numerical demonstrations in Excel to assist with teaching / learning concepts in statistics and geostatistics.

expert-gate

We introduce a model of lifelong learning, based on a Network of Experts. New tasks / experts are learned and added to the model sequentially, building on what was learned before. To ensure scalability of this process, data from previous tasks cannot be stored and hence is not available when learning a new task. A critical issue in such context, not addressed in the literature so far, relates to the decision of which expert to deploy at test time. We introduce a set of gating autoencoders that learn a representation for the task at hand, and, at test time, automatically forward the test sample to the relevant expert. This also brings memory efficiency as only one expert network has to be loaded into memory at any given time. Further, the autoencoders inherently capture the relatedness of one task to another, based on which the most relevant prior model to be used for training a new expert, with finetuning or learning without-forgetting, can be selected. We evaluate our method on image classification and video prediction problems.

exploiting_plume_structure

Supplementary code for our publication on exploiting plume structure for estimating gas source proximity. Reproduces all figures in that paper.

extraamas_2020

EXTRAAMAS 2020 Workshop source files for results and Figures

fairlearn

A Python package to assess and improve fairness of machine learning models.

falcon

Falcon: A practical log-based analysis tool for distributed systems

fastbook

Draft of the fastai book

faultseg

Using synthetic datasets to train an end-to-end CNN for 3D fault segmentation (We are working on an improved version!)

fbsnns

Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations

fcl-for-scikit-fuzzy

An FCL parser that generates scikit fuzzy rules (this is not a fork of scikit-fuzzy)

feast

Feature Store for Machine Learning

feast_pte

feature_engine

Feature engineering package with sklearn like functionality

featureselect

FeatureSelect

fel

Fast Entity Linker Toolkit for training models to link entities to KnowledgeBase (Wikipedia) in documents and queries.

fesapi

Allow access in reading and writing to Energistics standards data (mainly RESQML2.0, ETP1.2, some of WITSML2.0 and PRODML2.1)

ffdl

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes

fieldopt

New main repository for the FieldOpt project

fieldopt-research-open

FieldOpt C++ Optimization Framework [Open Research Version]