Search Results for "level set methods" - Page 4
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Showing 121 open source projects for "level set methods"
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Text Classification
All kinds of text classification models and more with deep learning
Text Classification is a deep learning repository focused on text classification models for NLP. It provides a broad set of baseline architectures that can be used to study, train, compare, and adapt classification approaches. The project supports both single-label and multi-label classification, making it useful for sentence-level and document-level tasks. It includes classic and advanced models such as fastText, TextCNN, BERT, TextRNN, RCNN, hierarchical attention networks, seq2seq attention, Transformers, dynamic memory networks, entity networks, ensembles, and boosting methods. ... -
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Opta
The next generation of Infrastructure-as-Code
Opta is an infrastructure-as-code framework. Rather than working with a low-level cloud configuration, Opta enables you to work with high-level constructs. Opta high-level constructs produce Terraform configuration files. This helps you avoid lock-in to Opta. You can write custom Terraform code or even take the Opta-generated Terraform and go your own way. Opta is a new kind of Infrastructure-as-Code (IaC) framework that lets engineers work with high-level constructs instead of getting lost... -
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ceph-ansible
Ansible playbooks to deploy Ceph, the distributed filesystem
Ansible playbooks for Ceph, the distributed filesystem. This project assumes you have a basic knowledge of how Ansible works and have already prepared your hosts for configuration by Ansible. After you’ve cloned the ceph-ansible repository, selected your branch and installed Ansible then you’ll need to create your inventory file, playbook and configuration for your Ceph cluster. The Ansible inventory file defines the hosts in your cluster and what roles each host plays in your Ceph cluster.... -
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A toolkit for building high-level compound widgets in Python using the Tkinter module. It contains a set of flexible and extensible megawidgets, including notebooks, comboboxes, selection widgets, paned widgets, scrolled widgets and dialog windows. Python megawidgets is Python 3 compatible through the Pmw 2 download. Pmw 1 is destined for Python 2. Both are now accessible through the new pypi compatible package (credits for which go to Andy Robinson and the team at ReportLab).
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Texar-PyTorch
Integrating the Best of TF into PyTorch, for Machine Learning
Texar-PyTorch is a toolkit aiming to support a broad set of machine learning, especially natural language processing and text generation tasks. Texar provides a library of easy-to-use ML modules and functionalities for composing whatever models and algorithms. The tool is designed for both researchers and practitioners for fast prototyping and experimentation. Texar-PyTorch was originally developed and is actively contributed by Petuum and CMU in collaboration with other institutes. A mirror... -
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PyExfil
A Python Package for Data Exfiltration
...Although most techniques and methods should be easily ported and compiled to various operating systems, some stable some experimental, the transmission mechanism should be stable on all techniques. Clone it, deploy on a node in your organization and see which systems can catch which techniques. -
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LockDown Browser Bypass
Browse the internet while using Respondus LockDown Browser
LockDown Browser Bypass is an experimental tool designed to bypass restrictions imposed by Respondus LockDown Browser on macOS systems by enabling access to external resources during controlled testing environments. The project demonstrates how system-level constraints enforced by proctoring software can be circumvented through alternative execution methods or environmental manipulation. It is part of a broader category of tools that explore the limitations and vulnerabilities of online exam monitoring systems. The repository focuses on providing a proof-of-concept implementation rather than a polished end-user application, highlighting technical feasibility over usability. ... -
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CBMPy
PySCeS Constraint Based Modelling
...Its architecture is both extensible and flexible using data structures that are intuitive to the biologist while transparently translating these into the underlying mathematical structures. . CBMPy implements popular analyses such as FBA, FVA, element/charge balancing, network analysis and model editing as well as advanced methods developed for the ecosystem modelling. CBMPy supports user interaction via: - interactive console or as a library for advanced use - GUI, visual representation of the model, analysis methods - a SOAP based webAPI exposes high level functionality via web services -
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NLP Best Practices
Natural Language Processing Best Practices & Examples
...The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in NLP algorithms, neural architectures, and distributed machine learning systems. -
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ChainerRL
ChainerRL is a deep reinforcement learning library
ChainerRL (this repository) is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. PFRL is the PyTorch analog of ChainerRL. ChainerRL has a set of accompanying visualization tools in order to aid developers' ability to understand and debug their RL agents. With this visualization tool, the behavior of ChainerRL agents can be easily inspected from a browser UI. Environments that support the subset of OpenAI Gym's interface (reset and step methods) can be used. -
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Orator
The Orator ORM provides a simple yet beautiful ActiveRecord implement.
The Orator ORM provides a simple yet beautiful ActiveRecord implementation. The Orator ORM is based on conventions to avoid the hassle of defining every single aspect of your models. It is inspired by the database part of the Laravel framework, but largely modified to be more pythonic. All you need to get you started is the configuration describing your database connections and passing it to a DatabaseManager instance. If you have multiple databases configured you can specify which one is... -
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TensorFlow Course
Simple and ready-to-use tutorials for TensorFlow
This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab. -
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RecNN
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like. -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. ... -
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PyRobot
An Open Source Robotics Research Platform
PyRobot is a high-level robotics API that simplifies controlling real and simulated robots through a consistent Python interface. Instead of fighting ROS internals, you call clear methods for things like base navigation, arm manipulation, and camera capture, and PyRobot handles the plumbing. It was built to make research repeatable on accessible platforms—most notably low-cost mobile manipulators—while still scaling to richer hardware. -
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Autologging
Easier logging and tracing of Python functions and class methods.
Autologging eliminates boilerplate logging setup code and tracing code, and provides a means to separate application logging from program flow and data tracing. Autologging provides two decorators and a custom log level: "autologging.logged" decorates a class to create a __log member. By default, the logger is named for the class's containing module and name (e.g. "my.module.ClassName"). "autologging.traced" decorates a class to provide automatic CALL/RETURN tracing for all class, static, and instance methods, as well as the special __init__ method (by default) "autologging.TRACE" is a custom log level (lower than logging.DEBUG) that is registered with the Python logging module when autologging is imported -
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Wally
Distributed Stream Processing
Wally is a fast-stream-processing framework. Wally makes it easy to react to data in real-time. By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). ... -
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...Algorithm implementation for population pharmacokinetic analysis: The current project describes the marriage between PBPK modeling and population-based statistical analysis. The latter is necessary for parameter estimation when individual-level data is available. A critical aspect of this coupling is the implementation of an algorithm that would allow the performance of population-based statistical analysis. Although novelty is encouraged in regards to the algorithm, proposals could entertain approaches such as: a. Implementing the non-linear mixed effects theory, b. Maximum log-likelihood algorithms (stiff, non-stiff Ordinary Differential Equation solving methods with linearization)
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A performance and usability focused Linux distribution based on 64-bit Debian testing. It is the successor to illume OS. To use the live ISO image, login to "root" with the password "antorca".
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The Software Testing Automation Framework (STAF) is a framework designed to improve the level of reuse and automation in test cases and test environments. The goal of STAF is to provide a complete end-to-end automation solution for testers.
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GT NLP Class
Course materials for Georgia Tech CS 4650 and 7650
This repository contains lecture notes, slides, assignments, and code for a university-level Natural Language Processing course. It spans core NLP topics such as language modeling, sequence tagging, parsing, semantics, and discourse, alongside modern machine learning methods used to solve them. Students work through programming exercises and problem sets that build intuition for both classical algorithms (like HMMs and CRFs) and neural approaches (like word embeddings and sequence models). ... -
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Use Vim as IDE
use vim as IDE
Use Vim As IDE is a comprehensive configuration repository (by YangYangWithGnu) that guides you how to turn Vim into a full-fledged Integrated Development Environment (IDE). The project isn’t just a single plugin; it’s more like a curated set of plugins, configuration tips, and workflow suggestions to enable syntax highlighting, smart code completion, project navigation, semantic search, file-switching, build-integration, undo-history, templating and more—particularly geared toward C/C++... -
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GNU Hyperbole: The Everyday Info Manager
Create hyperlinks just by dragging, find contacts instantly, ...
...It also includes a hierarchical, record-based contact manager, a rapid window and frame control system and a powerful multi-level auto-numbered outliner. -
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startrails
open game world to be set in a realistic environment
Discover a huge fictional game world and supply resources for its exploration. Unleash mysterious secrets or just race through the hills. This software is under development and thus neither complete nor bug-free. However, fun can occasionally be had. -
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Ionflux Tools
Metaprogramming framework for C++ development with Python bindings
...You can find the current version at https://github.com/TehFlux/iftools iftools is an umbrella project for various libraries and utilities that facilitate application development in C++ with full Python bindings. It provides a rich set of features while still maintaining compatibility with other frameworks through a very low overhead and a lack of "tricks". iftools uses its own, easily extensible template system to provide a rich set of metaprogramming techniques for implementing features above the class level.