Flow Libraries

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Flow Libraries

MDCS is an acronym for Mosaic Dataset Configuration Script and is the entry point to a collection of Python classes/libraries that could be consumed by a Python client application to complete a given workflow for creating a mosaic dataset, populating it with data, and setting all required/desired parameters.

SU2: An Open-Source Suite for Multiphysics Simulation and Design

Computational analysis tools have revolutionized the way we design engineering systems, but most established codes are proprietary, unavailable, or prohibitively expensive for many users. The SU2 tea…

Reusable workflow library for Django

Viewflow is a low-code, reusable component library for creating comprehensive business applications with ease. Built on top of Django, Viewflow simplifies development by providing pre-built component…

StackStorm (aka "IFTTT for Ops") is event-driven automation for auto-remediation, incident responses, troubleshooting, deployments, and more for DevOps and SREs. Includes rules engine, workflow, 160 integration packs with 6000+ actions (see https://exchange.stackstorm.org) and ChatOps. Installer at https://docs.stackstorm.com/install/index.html

StackStorm is a platform for integration and automation across services and tools. It ties together your existing infrastructure and application environment so you can more easily automate that envir…

Collective Mind (CM) is a collection of portable and extensible automation recipes with a unified and human-friendly interface and minimal dependencies to make it easier to compose, benchmark and optimize AI, ML and other applications and systems across diverse and continuously changing models, data sets, software and hardware (cloud/edge)

For example, you should be able to run the MLPerf inference benchmark on Linux, Windows and MacOS using a few CM commands: You can also run the same commands using a unified CM Python API:

Machine Learning Platform and Recommendation Engine built on Kubernetes

Seldon Server is a machine learning platform that helps your data science team deploy models into production. Seldon supports models built with TensorFlow, Keras, Vowpal Wabbit, XGBoost, Gensim and a…

A Django app that creates automatic web UIs for Python scripts.

Wooey is a simple web interface to run command line Python scripts. Think of it as an easy way to get your scripts up on the web for routine data analysis, file processing, or anything else. Wooey wa…

Scipion is an image processing framework to obtain 3D models of macromolecular complexes using Electron Microscopy (3DEM)

Porn images detector with python, tensorflow, scikit-learn and opencv.

Two python porn images (nudity) detectors. First one (pcr.py) use scikit-learn and opencv. I was able to get ~85% accuracy on markup with 1500 positive and 1500 negative samples. It use two machine-l…

An Open Source Machine Learning Framework for Everyone

TensorFlow was originally developed by researchers and engineers working within the Machine Intelligence team at Google Brain to conduct research in machine learning and neural networks. However, the…

A flexible, high-performance serving system for machine learning models

To note a few features: The easiest and most straight-forward way of using TensorFlow Serving is with Docker images. We highly recommend this route unless you have specific needs that are not address…

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

Use any of the following services. Next, run the following commands: Finally, start Jupyter: I recommend Python 3.7. If you follow the installation instructions above, that's the version you will get…

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

It was last updated to a fully running version in late October, 2021. You should refer to the Jupyter Notebooks in this repository rather than the book's source code, which is badly outdated and will…

Cast macOS and Linux Audio/Video to your Google Cast and Sonos Devices

This is what the system tray menu looks like: Check these images: There are two ways of installing this application: If you are using homebrew, it is possible to install the binary as follows: Addit…

✅ Command-line tool to manage Todo lists

Command-line tool to manage the Todo lists of your projects If you use several Python versions on your computer, create a virtual environment with the Python 3 interpreter: Activate the new environme…

A flexible, easy to use, automation framework allowing users to integrate their capabilities and devices to cut through the repetitive, tedious tasks slowing them down. #nsacyber

This documentation is intended as a reference for app and workflow developers as well as project contributors and operators. Here you will find walkthroughs, tutorials and other useful information ab…

U-Net: Convolutional Networks for Biomedical Image Segmentation

Setup Ubuntu 18.04, 16.04 and 14.04 with machine learning and robotics software plus user configuration. Includes ceres tensorflow ros caffe vrep eigen cudnn and cuda plus many more.

This contains a set of linux setup scripts consolidated from across the web to make it easy to set up a new computer for robotics and deep learning, with links to the original sources and brief descr…

[UNMAINTAINED] Automated machine learning for analytics & production

Automated machine learning for production and analytics auto_ml is designed for production. Here's an example that includes serializing and loading the trained model, then getting predictions on sing…

Python code for "Probabilistic Machine learning" book by Kevin Murphy

The notebooks needed to make all the figures are available at the following locations. You can use any of the following options to install the other requirements. Run Then install manually.

Test implementation of Deeply-Recursive Convolutional Network for Image Super-Resolution

Training highly deep CNN layers is so hard. However this paper makes it with some tricks like sharing filter weights and using intermediate outputs to suppress divergence in training. The model in th…

TensorFlow framework for training and serving machine learning models

There are some important principles that shape the design of the framework: OK, enough context... here is some information to get you started. Once you have a Python environment (recommendation: use …

TensorFlow framework for training and serving machine learning models

대학 강의를 위한 강의자료 및 소스코드 저장소 Python Lecture slide & code for University Student.

2016년 겨울방학 중앙대학교 Python 기초과목 구글 파이썬 스타일 가이드로 시작하는 프로그래밍 Ver 1.1.1 (Last Update 2018-06-14) 본 Repository는 GPL-3.0 라이센스를 따릅니다. 상업적, 교육용, 개인적인 사용이 가능합니다. 자세한 라이센스 제약사항은 본 글 하단을 참조하세요. 강의 슬라이드는 복습 =&g…

Image Super-Resolution Using Deep Convolutional Networks in Tensorflow https://arxiv.org/abs/1501.00092v3

Open source hardware and software platform to build a small scale self driving car.

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions. The don…

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

:computer: Learn to make machines learn so that you don't have to struggle to program them; The ultimate list

Machine Learning is a branch of Artificial Intelligence dedicated at making machines learn from observational data without being explicitly programmed. Machine learning and AI are not the same. Machi…

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