Search Results for "vector" - Page 7
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Showing 236 open source projects for "vector"
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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SentEval
A python tool for evaluating the quality of sentence embeddings
SentEval is a standardized toolkit for evaluating sentence embeddings across a wide spectrum of downstream tasks and probing tests. 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... -
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Magnitude
A fast, efficient universal vector embedding utility package
A feature-packed Python package and vector storage file format for utilizing vector embeddings in machine learning models in a fast, efficient, and simple manner developed by Plasticity. It is primarily intended to be a simpler / faster alternative to Gensim but can be used as a generic key-vector store for domains outside NLP. It offers unique features like out-of-vocabulary lookups and streaming of large models over HTTP. -
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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. After optimization, MAMA accurately simulated more than 87% of gene expression. See Kakei Y, Ogo Y, Itai RN, et al. (2013) Development of a novel prediction method of cis-elements to hypothesize collaborative functions of cis-element pairs in iron-deficient. ... -
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Machine Learning From Scratch
Bare bones NumPy implementations of machine learning models
...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. Because the code avoids external machine learning libraries, it exposes the full logic behind model training, optimization, and prediction processes. The project also provides examples and explanations that illustrate how the algorithms behave and how different components interact during training. -
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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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CakeChat
CakeChat: Emotional Generative Dialog System
...The first layer of the utterance-level encoder is always bidirectional. By default, CuDNNGRU implementation is used for ~25% acceleration during inference. Thought vector is fed into decoder on each decoding step. Decoder can be conditioned on any categorical label, for example, emotion label or persona id. May be initialized using w2v model trained on your corpus. Embedding layer may be either fixed or fine-tuned along with other weights of the network. -
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MUSE
A library for Multilingual Unsupervised or Supervised word Embeddings
...The code can align pre-trained monolingual embeddings (such as fastText) across dozens of languages and provides standardized evaluation scripts and dictionaries. By mapping languages into a common vector space, MUSE makes it straightforward to build cross-lingual applications where resources are scarce for some languages. The training and evaluation pipeline is lightweight and fast, so experimenting with different languages or initialization strategies is easy. Beyond dictionary induction, the learned embeddings are often used as building blocks for downstream tasks like classification, retrieval, or machine translation. -
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Python Data Science Tutorials
Common data analysis and machine learning tasks using python
...The collection begins with Python fundamentals and then moves into scientific computing, statistics, NumPy, pandas, data exploration, and visualization. Its machine learning sections cover practical algorithms and libraries, including regression, classification, clustering, support vector machines, and computer vision resources. Additional material addresses text mining, sentiment analysis, serialization with pickle, AutoML, regular expressions, and web scraping. The repository is organized by topic so learners can use it as a study roadmap or troubleshooting index. Many links document the earlier Python data science ecosystem, making the project especially valuable as a broad historical resource collection. -
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CrimeKgAssitant
Crime assistant including crime type prediction
...It organizes data around criminal charges, sentencing cases, legal question-and-answer pairs, and related legal information. A multiclass model predicts likely offense categories from written case descriptions using document embeddings and a support vector machine. Separate classifiers sort consultation questions into predefined legal categories before retrieving or generating relevant responses from the prepared knowledge base. The repository includes training scripts, inference programs, dictionaries, models, and utilities for building the question-answer database. Its published experiments use millions of case records and hundreds of thousands of consultation pairs. ... -
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TimingDrawer
Text based timing diagram generator
This tool generates timing diagrams for documenting hardware design. It reads the description from a text file with a simple syntax. It generates vector graphic (EPS, SVG or EMF format). It can be used in command line mode or with a GUI. It is written in Python and works on any platform. -
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Dynamic Routing Between Capsules
A PyTorch implementation of the NIPS 2017 paper
Dynamic Routing Between Capsules is a PyTorch implementation of the Capsule Network architecture originally proposed to address limitations in traditional convolutional neural networks. Capsule networks aim to improve how neural models represent spatial hierarchies and relationships between objects within images. Instead of scalar neuron activations, capsules output vectors that encode both the presence of features and their spatial properties such as orientation or pose. The repository... -
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Lihang
Statistical learning methods (2nd edition) [Li Hang]
...The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector machines, and hidden Markov models work in practice. In addition to code examples, the project contains supplementary materials such as formula references, glossaries of technical terms, and documentation explaining mathematical notation used throughout the algorithms. The repository also provides links to related research papers and references that expand on the theoretical background presented in the book. -
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Aprendiz de Mecânico
Adventure game prototype for mechanical technicians
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DreamStudio by Volocian Studios
Free yourself
Volocian believes first and foremost that financial status shouldn’t be a barrier to entry in multimedia content creation. Whether you want to design a product or website, record a band, remix a song, or produce a feature length movie with professional post production graphics and effects, Volocian™ wants to help, even if you’re using borrowed hardware with no previous experience. We provide affordable products and services for any budget, including cost-free solutions for education and demo... -
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node2vec
Learn continuous vector embeddings for nodes in a graph using biased R
The node2vec project provides an implementation of the node2vec algorithm, a scalable feature learning method for networks. The algorithm is designed to learn continuous vector representations of nodes in a graph by simulating biased random walks and applying skip-gram models from natural language processing. These embeddings capture community structure as well as structural equivalence, enabling machine learning on graphs for tasks such as classification, clustering, and link prediction. The repository contains reference code accompanying the research paper node2vec: Scalable Feature Learning for Networks (KDD 2016). ... -
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Box is a language specifically designed to make vector graphics easy plus a integrated development environment which facilitates the use of the language by interactively showing the graphical output. Box combines the convenience of drawing figures with the mouse with the convenience of describing them with a language tailored for vector graphics.
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Retrieval-Based Conversational Model
Dual LSTM Encoder for Dialog Response Generation
Retrieval-Based Conversational Model in Tensorflow is a project implementing a retrieval-based conversational model using a dual LSTM encoder architecture in TensorFlow, illustrating how neural networks can be trained to select appropriate responses from a fixed set of candidate replies rather than generate them from scratch. The core idea is to embed both the conversation context and potential replies into vector representations, then score how well each candidate fits the current dialogue, choosing the best match accordingly. Designed to work with datasets like the Ubuntu Dialogue Corpus, this codebase includes data preparation, model training, and evaluation components for building and assessing dialog models that can handle multi-turn conversations. -
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Leave A Trace Tools
Tools for reading the track data of the project "Leave a Trace"
...LAT XML Data can be downloaded here: https://leave-a-trace.charite.de/action/xml_dateien_der_traces/ ## Visualization tool: This project also contains a GUI-based visualization tool, which allows creation of custom vector data (SVG) from the given LAT data. This SVG data could, for example, be used for printing. If you want to use the visualization tool, as well, you'll need python2, along with the modules "numpy", "scipy" and "PyQt4". How to use: 1. Start the script 2. click the load button and select a compressed LAT-XML-file 3. click on "render SVG" (save somewhere) -
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PhaseSpace
Analyse dynamical systems, plot its phase space and critical points.
...PhaseSpace allows you to plot the phase space of the dynamical system you are studying, its critical points and the curves of slope zero and infinite.It can also plot the solutions of the system and it's vector field. To use PhaseSpace you'll need to have Python installed along with Matplotlib and Numpy. -
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Machine Learning framework in Python
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BFD Fibonacci Pattern Inkscape Extension
Inkscape plugin for generating the fibonacci pattern
This is an inkscape plugin, written by the software engineer for Beauty Full Day, for generating the Fibonacci Pattern. It is a flexible plugin for generating different sizes and allows for one to control how spread out the pattern is and how small to large each node can get. -
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Fluid2D
Fluid2D is the Swiss army knife of 2D CFD
...Its numerics has been chosen to yield to as small dissipation as possible allowing to simulate easily high Reynolds flows, much higher than any of its concurrents. High performances are achieved by writting most of the operations as matrix-vector multiplications, handled by numpy that itself relies on the highly optimized BLAS. -
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UniConvertor
Universal graphics translator
UniConvertor is an universal graphics translator. The project uses sK1 engine to convert one format to another. It has an import filters for: SVG, CDR, CDT, CMX, AI, XAR, CGM, WMF, XFIG, SK, SK1, SK2, CPL, ASE, ACO, JCW, GPL, SOC, SKP, PSD, XCF, PNG, JPG, TIFF, WEBP, BMP, PCX, PPM, XBM, XPM and export filters: SVG, AI, CDR, CMX, PDF, SK, SK1, SK2, CGM, WMF, CPL, ASE, ACO, JCW, GPL, SOC, SKP, PNG. This SourceForge project page is outdated. To download latest UniConvertor binaries, please... -
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GCompris : I got IT
Educational Software for children aged 2 to 10.
GCompris is a high quality educational software suite comprising of numerous activities for children aged 2 to 10. Some of the activities are game oriented, but nonetheless still educational.