Search Results for "data leakage detection python"
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Showing 17 open source projects for "data leakage detection python"
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Cut Your Data Warehouse Bill by 54%BigQuery delivers 54% lower TCO with serverless scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Push Code. Get a Production URL. Done.Skip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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PaperQA2
High accuracy RAG for answering questions from scientific documents
PaperQA2 is a package for doing high-accuracy retrieval augmented generation (RAG) on PDFs or text files, with a focus on the scientific literature. See our recent 2024 paper to see examples of PaperQA2's superhuman performance in scientific tasks like question answering, summarization, and contradiction detection. In this example we take a folder of research paper PDFs, magically get their metadata - including citation counts and a retraction check, then parse and cache PDFs into a... -
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Gwyddion
Scanning probe microscopy data visualisation and analysis
A data visualization and processing tool for scanning probe microscopy (SPM, i.e. AFM, STM, MFM, SNOM/NSOM, ...) and profilometry data, useful also for general image and 2D data analysis. -
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miRge3
Comprehensive analysis of small RNA sequencing data
An update to Python package to perform comprehensive analysis of small RNA sequencing data, including miRNA annotation, A-to-I editing, novel miRNA detection, isomiR analysis, visualization through IGV, processing Unique Molecular Identifieres (UMI), tRF detection and producing interactive graphical output. miRge3.0 is developed in python v3.8 and is a recent update of our previous version miRge2.0. -
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Firmware mod for the GWInstek GPP-x32x series lab bench supply.
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Go From Idea to Deployed AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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NuPIC
Numenta platform for intelligent computing
The Numenta Platform for Intelligent Computing (NuPIC) is a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources. For more information, see numenta.org or the NuPIC Forum. If you want... -
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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. -
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HistogramsApp
Application that generates KDE-PDP plots from geochronological data
HistogramsApp is a Python 3.6 application that generates (KDE and PDP) from geochronological data .HistogramsApp allows to interactively setup plot parameters such as the bandwidth and the peak detection sensibility. To cite the application please refer to: 1) https://www.tandfonline.com/doi/abs/10.1080/00206814.2021.1954556?journalCode=tigr20 Rodriguez-Corcho, A. -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists... -
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XIVO
X Inertial-aided Visual Odometry
XIVO is an open-source repository for visual-inertial odometry/mapping. It is a simplified version of Corvis [Jones et al.,Tsotsos et al.], designed for pedagogical purposes, and incorporates odometry (relative motion of the sensor platform), local mapping (pose relative to a reference frame of the oldest visible features), and global mapping (pose relative to a global frame, including loop-closure and global re-localization, this feature, present in Corvis, is not yet incorporated in XIVO).... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end. Migrate from on-prem or other clouds with free migration tools.
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2DFLT
Program for Normalization, Averaging and Editing of In Situ Data Sets
2DFLT it is first out of two programs which allows implementation of Phase Sensitive Detection (PSD) and/or Modulated Enhanced Diffraction (MED) techniques on the in situ data. This software allows collecting individual data files from in situ experiment into one dataset. After that this data set can be visualized, edited, normalized and averaged. Resulted data can be saved as one flat file (FLT-format) which can be used for PSD/MED calculations via 2DMED software... -
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This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...
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2DMED
Phase Sensitive Detection and Modulated Enhanced Diffraction Software
2DMED it is the second out of two programs which allows implementation of Phase Sensitive Detection (PSD) and/or Modulated Enhanced Diffraction (MED) techniques on the in situ data. This software takes normalized and averaged in situ data in flat file format (FLT) and performs PSD transformation which has been described in Urakawa, A.et al. Chem. Eng. Science 2008, 63, 4902. User can choose demodulation index k and perform several demodulation calculations. This is extremely important since... -
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QuickNXS
Polarized ToF reflectivity raw data analysis tool
Data evaluation tool for the magnetism reflectometer at the spallation neutron source (BL-4A@SNS). Reads raw nexus files (HDF5) of histogrammed or event mode data to create reflectivity curves and 2D Q-maps. -
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FineSplice
Enhanced splice junction detection and estimation from RNA-Seq data
FineSplice is a Python wrapper to TopHat2 geared towards a reliable identification of expressed exon junctions from RNA-Seq data, at enhanced detection precision with small loss in sensitivity. Following alignment with TopHat2 using known transcript annotations, FineSplice takes as input the resulting BAM file and outputs a confident set of expressed splice junctions with the corresponding read counts. -
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A free, industrial quality library for simulating articulated rigid body dynamics - for example ground vehicles, legged creatures, and moving objects in VR environments. It's fast, flexible & robust. Built-in collision detection.
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SpiKeDeteKt
An automatic spike detection program to be used with new KlustaKwik
This is an automatic spike detection program which takes account of probe geometry and produces a .mask file to be used with the new masked version of KlustaKwik. We recommend you use Python 2.6 or 2.7, e.g. a free academic version can be obtained from Entthought Python. The input files for SpiKeDeteKt are: .dat (raw data file) .probe (probe file, described below - user constructed) parameters.py (optional - otherwise it uses defaultparameters.py) SpiKeDeteKt outputs the following files: .fet.n (feature file) .mask.n (needed for using the new (masked) KlustaKwik) .clu.n (a trivial clue file where everything is put into a single cluster) .fmask.n (trial - float masks instead of binary, we are using this for testing masked KlustaKwik) .spk.n (spike file) .upsk.n (unfiltered spike waveform) .res.n (list of spike times) .xml (an xml file with all the parameters that can subsequently be used by neuroscope or klusters) .fil (highpass filtered data) .h5 ( -
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ViAmI-Server
Pattern recognition for ADL events
This software uses computer vision algorithms for mining sequence data from telemonitoring data with CBRs. We propose an approach which treats the detection of changes in behavior detected with a sensor/video fusion, which occur at radically different time-scales, through a CBR in two levels: low and high level. The system is always updating the database with the daily data.
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