A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
machine-learning
deep-learning
data-science
python
automated-machine-learning
natural-language-processing
hyperparameter-optimization
automl
jupyter-notebook
timeseries-forecasting
tuning
classification
finetuning
hyperparam
natural-language-generation
random-forest
regression
scikit-learn
tabular-data
Обновлено 2024-09-06 07:00:13 +03:00
A set of tools to use in Microsoft Azure Form Recognizer and OCR services.
machine-learning
typescript
machine-learning-algorithms
rpa
form-recognizer
labeling-tool
ocr-form-labeling
Обновлено 2024-09-04 06:49:14 +03:00
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
machine-learning
deep-learning
data-science
python
tensorflow
mlops
pytorch
hyperparameter-optimization
hyperparameter-tuning
machine-learning-algorithms
model-compression
nas
neural-architecture-search
neural-network
automated-machine-learning
automl
bayesian-optimization
deep-neural-network
distributed
feature-engineering
Обновлено 2024-07-03 13:54:08 +03:00
R powered custom visual based on rpart package
Обновлено 2024-04-16 11:25:49 +03:00
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
machine-learning
deep-learning
python
pytorch
hyperparameter-optimization
automated-machine-learning
automl
model-compression
nas
neural-architecture-search
darts
petridish
Обновлено 2023-12-22 22:29:11 +03:00
About Infer# is an interprocedural and scalable static code analyzer for C#. Via the capabilities of Facebook's Infer, this tool detects null dereferences, resource leaks, and thread-safety violations. It also performs taint flow tracking to detect critical security vulnerabilities like SQL injections.
Обновлено 2023-07-19 22:32:36 +03:00
Time Series Forecasting Best Practices & Examples
machine-learning
python
deep-learning
artificial-intelligence
r
best-practices
jupyter-notebook
automl
lightgbm
hyperparameter-tuning
model-deployment
prophet
retail
tidyverse
time-series
azure-ml
demand-forecasting
dilated-cnn
forecasting
Обновлено 2023-05-01 00:54:37 +03:00
Security configuration is complex. With thousands of group policies available in Windows, choosing the “best” setting is difficult. It’s not always obvious which permutations of policies are required to implement a complete scenario, and there are often unintended consequences of some security lockdowns. The SECCON Baselines divide configuration into Productivity Devices and Privileged Access Workstations. This document will focus on Productivity Devices (SECCON 5, 4, and 3). Microsoft’s current guidance on Privileged Access Workstations can be found at http://aka.ms/cyberpaw and as part of the Securing Privileged Access roadmap found at http://aka.ms/privsec.
Обновлено 2022-11-28 22:10:26 +03:00
Example of using HyperDrive to tune a regular ML learner.
Обновлено 2020-04-08 00:51:45 +03:00
Hyperparameter Tuning for Deep Learning
Обновлено 2020-02-05 03:19:52 +03:00
INACTIVE - http://mzl.la/ghe-archive - Planning for individual and small group engagement with Maker Party
Обновлено 2019-03-31 21:42:25 +03:00
DEPRECATED - Lunch etherpads in iframes
Обновлено 2017-02-16 21:28:17 +03:00
INACTIVE - http://mzl.la/ghe-archive - Tools to create ARPA models from cmu pocketsphinx dictionaries for proper g2p generation
Обновлено 2015-07-28 18:24:02 +03:00
DEPRECATED - Etherpad Open-Source Repository
Обновлено 2015-06-03 06:44:26 +03:00
INACTIVE - http://mzl.la/ghe-archive - Generates a Maker Party styled heatmap given the number of events by country.
Обновлено 2014-06-11 18:29:57 +04:00
DEPRECATED - An Etherpad based on node.js - Our goal is to make collaborative editing the standard on the web
Обновлено 2013-07-20 02:44:49 +04:00