Search Results for "data capture framework" - Page 2
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Showing 40 open source projects for "data capture framework"
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1
SentEval
A python tool for evaluating the quality of sentence embeddings
...It defines a simple interface—provide an encoder function from sentences to vectors—and then runs consistent training/evaluation loops for tasks like sentiment, entailment, paraphrase, and semantic textual similarity. The suite also contains linguistic probing tasks that illuminate what properties embeddings capture, such as tense, word order, or syntactic structure. Datasets are wrapped with unified preprocessing and metrics so results are comparable across papers and implementations. Because the interface is minimal, researchers can plug in encoders from any framework or language model and obtain a broad evaluation with little glue code. ... -
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MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,... -
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Python Crawler Tutorial Starts From Zero
Python crawler tutorial, taking you from zero to one
Python Crawler Tutorial Starts From Zero is a Chinese-language learning repository that teaches web crawling from introductory concepts through practical examples. Early lessons explain HTTP requests, request analysis, the Python Requests library, and common categories of extracted data. Separate chapters cover JSON processing and regular expressions for transforming responses into structured information. Practical exercises demonstrate crawlers for Douban movies, Baidu Tieba, and Baidu Translate. Broader project materials also address topics such as JavaScript reverse engineering, Selenium automation, OCR, MongoDB, and the Scrapy framework. ... -
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Graph Nets library
Build Graph Nets in Tensorflow
Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. ... -
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5
I3D models trained on Kinetics
Convolutional neural network model for video classification
...The project provides TensorFlow and Sonnet-based implementations, pretrained checkpoints, and example scripts for evaluating or fine-tuning models. It also offers sample data, including preprocessed video frames and optical flow arrays, to demonstrate how to run inference and visualize outputs. -
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backtrader
Python Backtesting library for trading strategies
backtrader is a Python framework for developing, backtesting, and running trading strategies. Its Cerebro engine coordinates strategies, data feeds, brokers, indicators, analyzers, and execution. Developers can combine multiple strategies, instruments, and timeframes while resampling or replaying market data. The framework includes a large indicator library, custom indicator support, analyzers, position sizing, commissions, and trading calendars. -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. ... -
8
SFD
S³FD: Single Shot Scale-invariant Face Detector, ICCV, 2017
S³FD (Single Shot Scale-invariant Face Detector) is a real-time face detection framework designed to handle faces of various sizes with high accuracy using a single deep neural network. Developed by Shifeng Zhang, S³FD introduces a scale-compensation anchor matching strategy and enhanced detection architecture that makes it especially effective for detecting small faces—a long-standing challenge in face detection research. The project builds upon the SSD framework in Caffe, with... -
9
Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual prediction). ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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10
Question Answering Corpus
Question answering dataset in "Teaching Machines to Read & Comprehend"
RC-Data is a dataset generation framework created by Google DeepMind to produce large-scale reading comprehension question-answer pairs from CNN and Daily Mail news articles. The dataset, introduced in the 2015 paper “Teaching Machines to Read and Comprehend” (Hermann et al., NIPS 2015), was among the first large corpora designed to train and evaluate machine reading and comprehension models. -
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Fast Artificial Neural Network Library is a free open source neural network library, which implements multilayer artificial neural networks in C with support for both fully connected and sparsely connected networks. Cross-platform execution in both fixed and floating point are supported. It includes a framework for easy handling of training data sets. It is easy to use, versatile, well documented, and fast. Bindings to more than 15 programming languages are available. An easy to read introduction article and a reference manual accompanies the library with examples and recommendations on how to use the library. Several graphical user interfaces are also available for the library.
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DBFrames is an application framework for building data aware applications for Windows Mobile devices. It uses PythonCE, SQLite and PocketPyGui. Version for Android (writen in Java): https://github.com/yurtk/dbfragments
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PyLibrary
Libraries for Python developers.
Development in Python (be it website or an App development or implementation of an automation framework) always involves certain operations like handling db queries, operations on web, development of data structures, windows operations (handing services, registries), logging and many more... What, if you have these libraries handy with you all the time? Just import and start using them.. In comes PyLibrary.. PyLibrary is a collection of infrastructure libraries that aid faster development in Python. ... -
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Addons to the Django Framework for mobile clients. MoGo was originally built to handle JP specific issues, but code to handle other locales are welcome as well. Developed and maintained by MARIMORE Inc http://www.marimore.co.jp THIS PROJECT HAS MOVED TO https://github.com/marimore/mobiledjango
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15
mini-filter-driver-framework
A mini filter driver development framework for you
EaseFilter File System Filter Driver Framework is a set of file system filter driver software development kit which includes file monitor filter driver, file access control filter driver, transparent file encryption filter driver, process filter driver and registry filter driver. The File Security Solution with the EaseFilter Comprehensive File Security SDK encompasses file security, digital rights management, encryption, file monitoring, file auditing, file tracking, data loss prevention, process monitoring and protection, and system configuration protection. ...
