Showing 265 open source projects for "method"

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  • 1
    Age and Gender Estimation

    Age and Gender Estimation

    Keras implementation of a CNN network for age and gender estimation

    ...We pose the age regression problem as a deep classification problem followed by a softmax expected value refinement and show improvements over direct regression training of CNNs. Our proposed method, Deep EXpectation (DEX) of apparent age, first detects the face in the test image and then extracts the CNN predictions from an ensemble of 20 networks on the cropped face.
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  • 2
    Chisel

    Chisel

    A collection of LLDB commands to assist debugging iOS apps

    Chisel is a collection of LLDB commands designed to assist you in the process of debugging iOS apps. All of the commands provided by Chisel come with verbose help. Be sure to read it when in doubt! You can add local, custom commands. There's also builtin support to make it super easy to specify the arguments and options that a command takes. See the border and pinvocation commands for example use. Developing commands, whether for local use or contributing to Chisel directly, both follow the...
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  • 3
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than...
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  • 4
    ENAS in PyTorch

    ENAS in PyTorch

    PyTorch implementation of "Efficient Neural Architecture Search

    ENAS in PyTorch is a PyTorch implementation of Efficient Neural Architecture Search (ENAS), a method that automates the design of neural network architectures through reinforcement learning and parameter sharing. The repository demonstrates how a controller network can explore a large search space and discover high-performing architectures while dramatically reducing the computational cost traditionally associated with neural architecture search.
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  • 5

    Microarray assosiated motif analyzer

    Cis-element prediction tool from microarray data

    We developed a novel clustering-free method, microarray-associated motif analyzer (MAMA), to predict novel cis-acting elements based on weighted sequence similarities and gene expression profiles in microarray analyses. Simulation of gene expression was performed using a support vector machine and based on the presence of predicted motifs and motif pairs. The accuracy of simulated gene expression was used to evaluate the quality of prediction and to optimize the parameters used in this method. ...
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  • 6
    mongoaudit

    mongoaudit

    A powerful MongoDB auditing and pentesting tool

    ...MongoDB is not exposing its version number. MongoDB version is newer than 2.4. TLS/SSL encryption is enabled. Authentication is enabled. SCRAM-SHA-1 authentication method is enabled.
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  • 7
    ...To measure the entire set of PTMs across diverse proteomes, software must overcome the dual challenges of covering enormous search spaces and distinguishing correct from incorrect spectrum interpretations. Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments. We applied TagGraph to a published human proteomic dataset of 25 million mass spectra and tripled confident spectrum identifications compared to its original analysis. We identified thousands of modification types on almost 1 million sites in the proteome.
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  • 8
    FuzzyWuzzy

    FuzzyWuzzy

    Fuzzy string matching in Python

    We’ve made it our mission to pull in event tickets from every corner of the internet, showing you them all on the same screen so you can compare them and get to your game/concert/show as quickly as possible. Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example...
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  • 9
    DEBay

    DEBay

    Deconvolutes qPCR data to estimate cell-type-specific gene expression

    DEBay: Deconvolution of Ensemble through Bayes-approach DEBay estimates cell type-specific gene expression by deconvolution of quantitative PCR data of a mixed population. It will be useful in experiments where the segregation of different cell types in a sample is arduous, but the proportion of different cell types in the sample can be measured. DEBay uses the population distribution data and the qPCR data to calculate the relative expression of the target gene in different cell types in...
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  • 10
    Orator

    Orator

    The Orator ORM provides a simple yet beautiful ActiveRecord implement.

    ...If you want to use the previous behavior just set the use_unicode configuration option to False. Once you have configured your database connection, you can run queries. To run a set of operations within a database transaction, you can use the transaction method which is a context manager.
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  • 11
    deep-q-learning

    deep-q-learning

    Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

    The deep-q-learning repository authored by keon provides a Python-based implementation of the Deep Q-Learning algorithm — a cornerstone method in reinforcement learning. It implements the core logic needed to train an agent using Q-learning with neural networks (i.e. approximating Q-values via deep nets), setting up environment interaction loops, experience replay, network updates, and policy behavior. For learners and researchers interested in reinforcement learning, this repo offers a concrete, runnable example bridging theory and practice: you can execute the code, play with hyperparameters, observe convergence behavior, and see how deep Q-learning learns policies over time in standard environments. ...
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  • 12
    Finite Element Method Magnetics

    Finite Element Method Magnetics

    Finite element analysis of electromagnetic devices

    Solves low frequency magnetic, electrostatic, heat flow, and current flow problems on 2D and axisymmetric domains via the finite element method.
    Downloads: 61 This Week
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  • 13

    WebExKit

    An HTML/CSS/JavaScript editor with preview window

    ...The editor shows a properly formed HTML page rather than separate editors for HTML, CSS and JavaScript. The parts go between the ```<body>, <style> and <script>``` tags. I prefer this method of working and one advantage is the ability to show a saved web page in a browser (on another device, possibly) by entering a "file://..." URL. Head to the Wiki for more information.
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  • 14
    namedtupledefs

    namedtupledefs

    Pacthed namedtuple for field defaults.

    The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2.
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  • 15
    namedtuplex

    namedtuplex

    Pacthed namedtuple for field defaults.

    The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2.
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  • 16
    namedtupledefs3

    namedtupledefs3

    Pacthed namedtuple for field defaults.

    The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python2 see namedtupledefs2.
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  • 17
    namedtupledefs2

    namedtupledefs2

    Pacthed namedtuple for field defaults.

    The namedtupledefs is a patched release of the standard collection.namedtuple with added support of default values for field. In addition a method _merge is supported for the combination of named tuples. For Python3 see namedtupledefs3 or namedtupledefs
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  • 18
    InferSent

    InferSent

    InferSent sentence embeddings

    InferSent is a supervised sentence embedding method that learns universal representations from Natural Language Inference data and transfers well to many downstream tasks. It uses a BiLSTM encoder with max-pooling to produce fixed-length sentence vectors that capture semantics beyond bag-of-words statistics. Trained on large NLI datasets, the embeddings generalize across tasks like sentiment analysis, entailment, paraphrase detection, and semantic similarity with simple linear classifiers. ...
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  • 19
    CCZero (中国象棋Zero)

    CCZero (中国象棋Zero)

    Implement AlphaZero/AlphaGo Zero methods on Chinese chess

    ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics.
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  • 20
    vid2vid

    vid2vid

    Pytorch implementation of our method for high-resolution

    vid2vid is a deep learning framework for high-resolution video-to-video translation that generates photorealistic videos from structured inputs such as semantic maps, pose sequences, or edge maps. Built on top of image-to-image translation techniques like pix2pixHD, it extends these ideas into the temporal domain by ensuring consistency across video frames. The system can synthesize complex outputs such as realistic talking faces, human motion animations, or dynamic street scenes by learning...
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  • 21

    Safe Harbor Deidentification

    Safe Harbor Deidentification for medical documents

    Phalanx - Deidentify Safe Harbor Deidentification Mode of Phalanx is an abridged pipeline of NLP annotators culminating in NER annotators which write output of text offsets. It uses the Safe Harbor deidentification method.
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  • 22
    AeroPython

    AeroPython

    Classical Aerodynamics of potential flow using Python

    The AeroPython series of lessons is the core of a university course (Aerodynamics-Hydrodynamics, MAE-6226) by Prof. Lorena A. Barba at the George Washington University. The first version ran in Spring 2014 and these Jupyter Notebooks were prepared for that class, with assistance from Barba-group PhD student Olivier Mesnard. In Spring 2015, we revised and extended the collection, adding student assignments to strengthen the learning experience. The course is also supported by an open learning...
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  • 23

    FOSS license

    FOSS license and sentence token

    We propose a method to mark the comments of license as sentence-token. We use the term sentence-token to refer to a sentence of a known license. A license (both by-inclusion or by-reference) is a sequence of sentence-tokens. Sentence-tokens are generalized using one or more regular expressions. we propose an idea for license identification based on the analysis of each sentence in the license statement of a source code file.
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  • 24

    Autologging

    Easier logging and tracing of Python functions and class methods.

    ..."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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  • 25
    Virtual Laboratory Environment

    Virtual Laboratory Environment

    A multi-modeling and simulation environment to study complex systems

    VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. The models can be developed with the DEVS formalism or with the classical...
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