Search Results for "anpr using python" - Page 3
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Showing 97 open source projects for "anpr using python"
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Swiple
Swiple enables you to easily observe, understand, validate data
Swiple is an automated data monitoring platform that helps analytics and data engineering teams seamlessly monitor the quality of their data. With automated data analysis and profiling, scheduling and alerting, teams can resolve data quality issues before they impact mission critical resources. Experience hassle-free integration with Swiple's zero-infrastructure and zero-code setup. Seamlessly incorporate data quality checks into your existing workflows without any coding or infrastructure... -
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SentimentAnalysis-Rick&Morty
Rick & Morty Sentiment Analysis - End-of-Degree Project - UNIR
...Through the extraction of information from textual data, it becomes possible to identify and comprehend the sentiments and emotions conveyed. In this end-of-degree work, we analyze and classify the dialogue of characters in an English-language television series as "Rick and Morty" using Python. The objective is to identify and categorize the feelings and emotions expressed in the text, comparing the human perception of the characters' personalities with the results obtained using natural language processing techniques. -
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ScikitLearn.jl
Julia implementation of the scikit-learn API
The scikit-learn Python library has proven very popular with machine learning researchers and data scientists in the last five years. It provides a uniform interface for training and using models, as well as a set of tools for chaining (pipelines), evaluating, and tuning model hyperparameters. ScikitLearn.jl brings these capabilities to Julia. Its primary goal is to integrate both Julia- and Python-defined models together into the scikit-learn framework. -
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EBSP Indexer
GUI for processing and indexing EBSP from SEMs
EBSP Indexer is a graphical user interface that allows for processing and indexing of Electron backscatter patterns which are generated by scanning electron microscopes. Its goal is to make the rich functionality of the open-source library kikuchipy more accessible to users, without requiring knowledge of python or the library itself. Contribute by using our DOI: https://zenodo.org/record/7925262 -
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DataMelt
Computation and Visualization environment
...Elements of symbolic computations using Octave/Matlab scripting are supported. -
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SQLBucket
Lightweight library to write, orchestrate and test your SQL ETL
...That folder will contain all your SQL ETL. The python file where you create your SQLBucket object is also a good place to instantiate your command line interface. -
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TSNE-CUDA
GPU Accelerated t-SNE for CUDA with Python bindings
This repo is an optimized CUDA version of FIt-SNE algorithm with associated python modules. We find that our implementation of t-SNE can be up to 1200x faster than Sklearn, or up to 50x faster than Multicore-TSNE when used with the right GPU. You can install binaries with anaconda for CUDA version 10.1 and 10.2 using conda install tsnecuda -c conda-forge. Tsnecuda supports CUDA versions 9.0 and later through source installation, check out the wiki for up to date installation instructions. ... -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. ... -
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StreamAlert
StreamAlert is a serverless, realtime data analysis framework
StreamAlert is a serverless, real-time data analysis framework that empowers you to ingest, analyze, and alert on data from any environment, using data sources and alerting logic you define. Computer security teams use StreamAlert to scan terabytes of log data every day for incident detection and response. Incoming log data will be classified and processed by the rules engine. Alerts are then sent to one or more outputs. Rules are written in Python; they can utilize any Python libraries or functions. ... -
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pydatascope
Software oscilloscope using Python and tkinter
Software oscilloscope using Python and tkinter. Supports multiple sources: socket, file, audio, USB. Displays data by samples, time or frequency. Scales the input automatically or manually. -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
...They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK. -
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Jupytab
Display in Tableau data from Jupyter notebooks
Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab. -
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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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SageMaker Containers
Create SageMaker-compatible Docker containers
Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to... -
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Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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GEOMS2
Geostatistics and geosciences modeling software
GEOMS2 is a geostatistics and geosciences modeling software. Provides interface for grid (mesh), point, surface and data (non-spatial) objects. It has a 3D viewer and 2D plots using the well known Python engines Mayavi and Matplotlib. It has several functions to manipulate your data as well as provide univariate and multivariate analysis. NOTE: The software is still an early beta. Please tell us if you found a bug. Download datasets for students of Geostatistics 2017 (Petroleum Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Petroleum.zip/download Download datasets for students of Geostatistics 2017 (Geology and Mining Engineering): https://sourceforge.net/projects/geoms2/files/Geostatistics_Mining.zip/download Old: http://sourceforge.net/projects/geoms2/files/SETS_geoestatistica2_2015.7z/download https://sites.google.com/site/cmrpsoftware/downloads/Quarry_sets.7z?... -
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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... -
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CloverDX
Design, automate, operate and publish data pipelines at scale
...CloverDX offers 100+ specialized components which can be further extended by creation of "macros" - subgraphs - and libraries, shareable with 3rd parties. Simple data manipulation jobs can be created visually. More complex business logic can be implemented using Clover's domain-specific-language CTL, in Java or languages like Python or JavaScript. Through its DataServices functionality, it allows to quickly turn data pipelines into REST API endpoints. The platform allows to easily scale your data job across multiple cores or nodes/machines. Supports Docker/Kubernetes deployments and offers AWS/Azure images in their respective marketplace -
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fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and... -
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xmgrace python interface
xmgrace and qtgrace plotting interface in python
This is a python module providing a nearly complete interface to the graphing program xmgrace and the new qtgrace (great project... grace works under windows, too, now!). It allows creation of grace plots from within python, which can be customized using python, or through grace after creation. -
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Vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python
Data science solutions, insights, dashboards, machine learning, deployment. We start at 100GB. Vaex is a high-performance Python library for lazy Out-of-Core data frames (similar to Pandas), to visualize and explore big tabular datasets. It calculates statistics such as mean, sum, count, standard deviation etc, on an N-dimensional grid for more than a billion (10^9) samples/rows per second. Visualization is done using histograms, density plots and 3d volume rendering, allowing interactive exploration of big data. ... -
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Clustergrammer
An interactive heatmap visualization built using D3.js
Clustergrammer is a visualization library built using D3.js that enables intuitive interaction with high-dimensional data. Clustergrammer was built with biological data in mind. Clustergrammer is a web-based tool for visualizing high-dimensional data (e.g. a matrix) as an interactive and shareable hierarchically clustered heatmap. Clustergrammer's front end (Clustergrammer-JS) is built using D3.js and its back-end (Clustergrammer-PY) is built using Python. -
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Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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Illustrated Algorithms
Interactive algorithm visualizations
Inspired by Grokking Algorithms and python-execution-trace, this project aims to reveal the mechanics behind algorithms via interactive visualizations of their execution. Visual representations of variables and operations augment the control flow, alongside actual source code. You can fast forward and rewind the execution to closely observe how an algorithm works. The same code that is displayed next to the illustration is also decorated using babel-plugin-trace-execution and executed to record the context at every step. ... -
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Hetionet
Hetionet: an integrative network of disease
Hetionet is a hetnet — network with multiple node and edge (relationship) types — which encodes biology. The hetnet was designed for Project Rephetio, which aims to systematically identify why drugs work and predict new therapies for drugs. The JSON and Neo4j formats contain node and edge properties, which are absent in the TSV and matrix formats, including licensing information. Therefore the recommended formats are JSON and Neo4j. Our hetio package in Python reads the JSON format, but it...
