Search Results for "anpr using python" - Page 2
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Showing 96 open source projects for "anpr using python"
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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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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Hello AI World
Guide to deploying deep-learning inference networks
Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. -
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Binarytree
Python library for studying Binary Trees
...Traverse trees using different algorithms. -
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Machine Learning PyTorch Scikit-Learn
Code Repository for Machine Learning with PyTorch and Scikit-Learn
Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. -
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Showtime
A Minor Project made in Python using OMDb API and Tkinter for Frontend
A Minor Project made in Python using Tkinter for frontend which fetches Data about Movies/TV-Series from an Online Database and uses the OMDB REST API and pyImdb to show Information about movies. Github : https://github.com/Cyborg117/Showtime -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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EduData
Datasets in Education and convenient interface for dataset
Datasets in Education and convenient interface for downloading and preprocessing dataset in education. The CLI tools to quickly convert the "raw" data of the dataset into "mature" data for knowledge tracing task. The "mature" data is in json sequence format and can be modeled by XKT and TKT(TBA) The analysis dataset tool only supports the json sequence format. To check the following statical indexes of the dataset. In order to better verify the effectiveness of the model, the dataset is... -
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Gato (Graph Animation Toolbox): Animate graph algorithms for example for computing shortest paths, minimal spanning trees, maximum flows or maximal cardinality or weight matchings. Create your own animations using the Animated Data Structures (ADS).
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wav2letter++
Facebook AI research's automatic speech recognition toolkit
First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. -
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IPython
Command shell for interactive computing in multiple languages
IPython provides a rich toolkit to help you make the most of using Python interactively. Comprehensive object introspection. IPython provides input history, persistent across sessions. Caching of output results during a session with automatically generated references. Extensible tab completion, with support by default for completion of python variables and keywords, filenames and function keywords. -
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
Quantitative-Notebooks is a curated set of Jupyter notebooks focused on quantitative finance, algorithmic investing, and data-driven portfolio analysis. While each individual notebook is aimed at practical finance workflows, the overall repository helps practitioners and learners use Python, pandas, and numerical libraries to build, test, and evaluate financial strategies using historical market data. The notebooks typically showcase how to perform backtesting, factor analysis, risk assessment, and other quantitative workflows in a reproducible, exploratory format. Because quantitative analysis often requires visualization, statistics, and time series processing, these notebooks also serve as templates for real financial research and strategy prototyping. ... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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This project is intended to provide code to be used with MySQL and Python to create a database of major league baseball game events which are freely provided by the mlb.com Gameday application. Older version also support creating a retrosheet.org database but that is no longer supported. All major and minor league pitch location and game statistic data can be downloaded using BBOS. Installation Videos!
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Tensorflow and deep learning
A crash course in six episodes for software developers
Tensorflow and deep learning repository is an educational deep learning crash course designed to help software developers quickly understand and apply machine learning concepts without requiring advanced academic background. It is structured as a series of guided lessons that combine theoretical explanations, practical examples, and runnable code, allowing learners to build intuition while actively experimenting with models. The repository covers core neural network concepts such as weights,... -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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A Machine Learning Course with Python
A course about machine learning with Python
The purpose of this project is to provide a comprehensive and yet simple course in Machine Learning using Python. Machine Learning, as a tool for Artificial Intelligence, is one of the most widely adopted scientific fields. A considerable amount of literature has been published on Machine Learning. The purpose of this project is to provide the most important aspects of Machine Learning by presenting a series of simple and yet comprehensive tutorials using Python. ... -
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Scikit-learn Tutorial
An introductory tutorial for scikit-learn
Scikit-learn Tutorial contains the materials for Jake VanderPlas’s introductory scikit-learn tutorial, originally used at major Python conferences. It provides a collection of notebooks that walk attendees from basic machine-learning concepts into practical modeling using the scikit-learn library. The tutorial covers data preparation, model fitting, evaluation, and common algorithms such as classification, regression, clustering, and dimensionality reduction. It is designed for people who already have a working Python environment and some familiarity with NumPy, SciPy, and Matplotlib. ... -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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Pydicom by examples
Basic and intermediate examples of DICOM library with Jupyter
Basic and intermediate examples to read, modify and write DICOM files with Python code using Jupyter - To install Jupyter - https://jupyter.org/install ====== All examples are based on Pydicom. An open source library - https://pydicom.github.io/ -
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The Deep Review
A collaboratively written review paper on deep learning, genomics, etc
This repository is home to the Deep Review, a review article on deep learning in precision medicine. The Deep Review is collaboratively written on GitHub using a tool called Manubot (see below). The project operates on an open contribution model, welcoming contributions from anyone. To see what's incoming, check the open pull requests. For project discussion and planning see the Issues. As of writing, we are aiming to publish an update of the deep review. We will continue to make project... -
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Python Cookbook
Python Cookbook, 3rd edition translation
Translators have always insisted on using Python 3 because it represents the future of Python. Although backward compatibility is its flaw, this situation will change sooner or later, and the future of Python 3 needs everyone's help and support. At present, most of the tutorial books on the market and online manuals are basically 2.x series, and there are few books based on 3.x series. -
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Acoustic Research Tool (ART)
Acoustic Simulation Library for Frequency and Time Domain Simulations.
ART is a flexible simulation framework for wind instruments. It includes a growing library of modelling elements. So far bore discontinuities, branches, tone holes, cylindrical and conical tubes, Bessel horns and bent tubes are available for frequency domain modelling. In the time domain generic bidirectional propagation elements, scattering elements, fractional delays, convolution with reflection functions and general z-domain networks are available and can be described using MuParserX... -
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Python Machine Learning book
The book code repository and info resource
What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning. From theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. This is not... -
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GNU Solfege is *free* ear training software written in Python 3.4 using the Gtk+ 3 toolkit. The program is designed to be easily extended with lesson files (data files), so the user can create new exercises.
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In programming assignments, students tend to copy from one another as they are given the same set of questions. This conduct should not be allowed as it is an individual assignment and each student must complete on his own. The existing program is available to detect plagiarism through source code similitude. However, it is hard to detect similarity in source code especially if the number of students is high. Furthermore, it is better to prevent plagiarism before it is committed. The...
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Salstat2
statistical package designed for the end user, multiplatform
Salstat2 is an statistical package written in python and designed for the end user It has a graphical user interface and also it is scriptable, It's multiplatform, It has a graphic system inherited from matplotlib, It allows you to use different libraries like numpy - for numerical calculations, it also lets you to interact with Microsoft Excel (R) by using a com client under windows(R) platform and finally you can create your own dialogs by using the interactive shell or the script panel. -
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Collective Mind Technology
plugin-based framework for systematic and reproducible experimentation
New version moved to http://github.com/ctuning/ck Collective Mind framework (cM) is an open-source plugin-based schema-free repository and infrastructure for collaborative, systematic and reproducible research and experimentation. This 3rd version (started in 2006) helps to implement, preserve, share and reproduce the whole experimental setup as connected modules and data. cM uses crowdsourcing to leverage knowledge and computational resources of multiple users. For example, it... -
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ODS3 Virtual Machine Challenge
Virtual Machine Image To Test Penetration Skills
The ODS3 Virtual Machine Challenge are downloadable images that can be run as VMWare or VirtualBox instances. The Idea behind the challenge is to test and exercise web application penetration testing in a controlled environment. These images are great for cyber security students, penetration testers and hobbyist. Care should be taken if installed on an Internet access host as the application are purposely vulnerable to attack and exploitation.
