Search Results for "patterns" - Page 10
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Showing 295 open source projects for "patterns"
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Makani
Makani was developed a commercial-scale airborne wind turbine
Makani was an ambitious Google X project that sought to harness wind energy using airborne wind turbines — autonomous kites capable of generating power while flying in crosswind patterns. This open-source repository contains the complete software stack that powered Makani’s research and flight systems, including the flight simulator, autopilot controller, avionics firmware, visualization tools, and ground control software. The software enables simulation, control, and analysis of the Makani M600 turbine system, designed to operate offshore and autonomously manage complex aerodynamic behaviors. ... -
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interactive-coding-challenges
120+ interactive Python coding interview challenges
...Problems span arrays, strings, stacks, queues, linked lists, trees, graphs, dynamic programming, and more, mirroring common interview themes. Many challenges include hints and reference solutions so you can compare approaches and learn idiomatic patterns. The structure encourages incremental improvement—start with a brute-force idea, then refine to optimal time and space complexity. It serves both as a self-study path and as a warm-up bank for interview prep or coding katas. -
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StellarGraph
Machine Learning on Graphs
StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. ... -
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HyLiTE
Hybrid Lineage Transcriptome Explorer
...Allopolyploidy describes the formation of a new hybrid organism from the union of two or more different parents. Allopolyploid species carry multiple copies of each gene (homeologs), which often exhibit unusual expression patterns. Homeolog expression levels can technically be determined from next generation sequencing data (RNA-seq), but in practice, assigning reads to one homeolog over another is extremely challenging, particularly on a whole-genome scale. HyLiTE automates this process, and allows gene expression patterns to be explored even in very complex allopolyploid species. -
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DNSGen
Intelligent DNS permutation tool for subdomain discovery
...These generated permutations help identify hidden or unlisted services that may not appear in standard DNS queries or public records. DNSGen applies multiple permutation techniques to create realistic domain combinations based on modern infrastructure naming patterns, including cloud environments, DevOps tools, and microservice architectures. It can also extract meaningful keywords from existing domain names and incorporate them into newly generated permutations. The resulting domain list can be further processed by DNS resolution tools such as MassDNS to determine which generated domains actually exist. -
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Python Patterns
A collection of design patterns/idioms in Python
Python-Patterns is a repository collecting implementations of many classical design patterns and idioms, written in Python. It serves as an educational resource: showing how to implement creational, structural, behavioral, testability, and other patterns in a Pythonic style (or sometimes less so), illustrating trade-offs, different styles, and use cases. -
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Image Quality Assessment
Convolutional Neural Networks to predict aesthetic quality of images
...The goal of the project is to automatically evaluate images based on perceived quality factors such as composition, clarity, and visual appeal. Instead of relying on simple image statistics, the system learns patterns that correlate with human judgments about image aesthetics and technical quality. The repository includes code for training models, performing inference, and evaluating predicted scores against labeled datasets. It also provides utilities for image preprocessing and data management that help prepare datasets for training deep learning models. -
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BlockCheck
Russian ISP blocking type checker
...The tool was designed for a specific network environment and is explicitly not useful outside Russia. It runs tests that help distinguish different blocking methods, such as DNS manipulation, IP blocking, HTTP blocking, TCP reset behavior, and deeper filtering patterns. The repository is now archived and marked as not currently working, so it should be treated as a historical and diagnostic reference rather than a maintained utility. Its value is strongest for people studying network censorship, ISP filtering behavior, and the technical mechanics of access restriction. Because test results could be affected by circumvention tools, the project warns users not to run it while bypass systems are enabled. -
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AIAlpha
Use unsupervised and supervised learning to predict stocks
...It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting market data, transforming financial indicators into machine learning features, and training models to identify patterns that may predict market trends. It also demonstrates how models can be evaluated through backtesting frameworks that simulate how a strategy would perform using historical market conditions. By combining financial analytics with machine learning algorithms, the repository illustrates the process of building data-driven investment strategies. -
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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pytorch-examples
Simple examples to introduce PyTorch
...By emphasizing readable code, the repository helps users understand how PyTorch’s imperative programming style enables flexible model development. It also serves as a quick reference for common patterns and techniques used in deep learning workflows. The project aligns with PyTorch’s philosophy of combining usability with performance and flexibility. Overall, pytorch-examples is an essential learning resource for anyone working with PyTorch. -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. Advanced sections touch on neural networks and... -
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Code Catalog in Python
Algorithms and data structures for review for coding interview
code-catalog-python serves as a grab-bag of small, readable Python examples that illustrate common algorithms, data structures, and utility patterns. Each snippet aims to be self-contained and easy to study, with clear inputs, outputs, and the essential logic on display. The catalog format lets you scan for an example, copy it, and adapt it to your use case without wading through a large framework. It favors clarity over micro-optimizations so learners can grasp the idea before worrying about edge performance. ... -
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ComplexEventExtraction
Expression pattern collection of Chinese compound event extraction
ComplexEventExtraction is a Chinese NLP project for identifying relationships between events expressed in compound sentences. It defines patterns for causal, conditional, sequential, contrastive, and parallel event structures. The system uses explicit connective words and phrase combinations to split text into linked event pairs. Extracted results can support event graphs that represent how situations develop, conflict, or depend on one another. The repository catalogs hundreds of linguistic patterns and demonstrates them on a large Chinese news corpus. ... -
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Dynamic Routing Between Capsules
A PyTorch implementation of the NIPS 2017 paper
...The repository implements the dynamic routing algorithm between capsules, which allows lower-level features to route their outputs to higher-level structures that best represent the detected patterns. This approach enables the model to capture part-to-whole relationships in visual data more effectively than standard CNNs. The project serves primarily as a research implementation that demonstrates how capsule networks can be built and trained using modern deep learning frameworks. -
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Django JET
Modern responsive template for the Django admin interface
...So if you don't want to comply with that we can provide you a commercial license (visit the Home page). The commercial license is designed for using Django JET in commercial products and applications without the provisions of the AGPLv3. Add URL-pattern to the URL patterns of your Django project urls.py file (they are needed for related–lookups and autocomplete). Dashboard is located into a separate application. So after a typical JET installation it won't be active. Add URL-pattern to the urlpatterns of your Django project urls.py file (they are needed for related–lookups and autocomplete). -
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Bracelet Generator
A friendship bracelet pattern designer.
Bracelet Generator is a friendship bracelet pattern designer. It enables you to easily design your own patterns, add rows and strings, change the colors. The pattern can also be symmetrized. With the two-colored motif editor, create your motif and the pattern will automatically be generated. The motif can be rotated and symmetrized. The patterns can be exported in .png, .jpeg and .ps. -
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Sorter
Easy and fast file organisation and management in a few mouse clicks
...You can put all letters documents into one folder, all images with the word home into another, all music by one artist in yet another folder, etc. Sorter organises these files into folders which are grouped according to one or more of the following patterns: a common word in the file names, the file type/format, a custom name and the category of the file formats. -
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tinfoleak
OSINT tool for extracting and analyzing Twitter intelligence data
...Once the data is gathered, tinfoleak organizes it into structured information that can support intelligence analysis and investigative research. tinfoleak is capable of analyzing user activity, relationships, and behavioral patterns to reveal insights about accounts and their interactions on the platform. It also processes content such as hashtags, mentions, media files, and metadata to identify trends and relevant connections. Additional analysis features help uncover geolocation information, visited places, and user movement patterns when location data is available. -
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jsondata
Modular JSON by trees and branches, pointers and patches
...Provides the assembly of modular patch entries and the serialization of resulting patch lists. - JSONDiff - Diff utility for JSON data. - JSONSearch - Search utility JSON patterns. Online documents: https://jsondata.sourceforge.io/ -
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FAKE2DB
Create custom test databases that are populated with fake data
Generate fake but valid data filled databases for test purposes using most popular patterns(AFAIK). Current support is sqlite, mysql, postgresql, mongodb, redis, CouchDB. The installation through pypi retrieves 'fake-factory' as a main dependency. db argument takes 6 possible options, sqlite, mysql, postgresql, mongodb, redis, CouchDB. name argument is OPTIONAL. When it is absent fake2db will name db's randomly. host argument is OPTIONAL. -
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PassGAN
A Deep Learning Approach for Password Guessing
PassGAN is a research implementation of a generative adversarial network trained to model human password patterns. It reproduces ideas from the paper “PassGAN: A Deep Learning Approach for Password Guessing” using a modified Wasserstein GAN implementation. The repository includes scripts for training models and generating candidate password samples from learned distributions. A pretrained model based on the RockYou dataset is provided for reproducing experiments. -
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BlockSparse
Efficient GPU kernels for block-sparse matrix multiplication
...The idea is to exploit block-level sparsity — i.e. treat matrices or weight tensors as composed of blocks, many of which may be zero or unused — to save compute and memory when sparsity patterns are structured. This is particularly useful in models like Sparse Transformers, where attention matrices or intermediate layers may adopt block-sparse patterns to scale better. The repo implements both blocksparse and blockwise convolution/transpose-convolution primitives, with support for preparing, executing, and verifying those ops on NVIDIA GPUs. ... -
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Microblog
Microblogging application developed in my Flask Mega-Tutorial series
Microblog is a Flask-based social blogging application that serves as the companion example project to the author’s Flask tutorial book, demonstrating how to build a production-ready web application with features typical of modern social systems. The project includes user registration and login, password hashing, profile editing, and avatar support, but it goes deeper by illustrating how to implement following/follower relationships, posting short messages, and displaying personalized feeds.... -
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bulbea
Deep Learning based Python Library for Stock Market Prediction
...The library provides tools for retrieving financial time series data, preprocessing market data, and training predictive models that estimate future price movements. bulbea integrates common machine learning frameworks such as TensorFlow and Keras to build neural network models capable of learning patterns in historical financial data. It includes utilities for splitting datasets, normalizing time series, and training models such as recurrent neural networks that can capture temporal dependencies in market behavior. The library also incorporates sentiment analysis capabilities that analyze social media data, particularly from Twitter, to estimate public sentiment toward financial assets. -
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To create an Open Source and Free solution for the analysis of woven fabric stuctures. Included will be the ability to view the weave structure in 2D, 3D and profile as well as print and save the drafts (patterns).
