Search Results for "python-ldap" - Page 149
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Showing 21184 open source projects for "python-ldap"
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series... -
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A simple music player
Music Player by Mood from YoutubeMusic
A simple music player with a GUI (PyQy6) to listen to music, depending on the selected mood. The program is based on YouTube Music playlists. -
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fpyprog
Program for statistic and visual analysis
Example of program for statistic and visual analysis on Python -
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pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
Python 3 code to reproduce the figures in the books Probabilistic Machine Learning: An Introduction (aka "book 1") and Probabilistic Machine Learning: Advanced Topics (aka "book 2"). The code uses the standard Python libraries, such as numpy, scipy, matplotlib, sklearn, etc. Some of the code (especially in book 2) also uses JAX, and in some parts of book 1, we also use Tensorflow 2 and a little bit of Torch. See also probml-utils for some utility code that is shared across multiple notebooks. -
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Solo Miner
Solo Miner V2
New Version Solo Miner with High Speed for mining Bitcoin With all System -
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Catalyst
Accelerated deep learning R&D
... something totally new. Catalyst is compatible with Python 3.6+. PyTorch 1.1+, and has been tested on Ubuntu 16.04/18.04/20.04, macOS 10.15, Windows 10 and Windows Subsystem for Linux. It's part of the PyTorch Ecosystem, as well as the Catalyst Ecosystem which includes Alchemy (experiments logging & visualization) and Reaction (convenient deep learning models serving). -
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant... -
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PY-Nodes
Code for finding nodes in a material using first-principle approach.
PY-Nodes is a Python 3 based code designed for searching nodes (bands-degenerate points) associated with two or more bands in a given material using the first-principle approach. This code is helpful in efficient searching of the nodes present in the topological semimetals such as- Weyl semimetals, Dirac semimetals & nodal-line semimetals. The code is presently interfaced with the WIEN2k package. The algorithm of the code is based on the Nelder-Mead’s function-minimization approach. The code... -
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gplearn
Genetic Programming in Python, with a scikit-learn inspired API
gplearn implements Genetic Programming in Python, with a scikit-learn-inspired and compatible API. While Genetic Programming (GP) can be used to perform a very wide variety of tasks, gplearn is purposefully constrained to solving symbolic regression problems. This is motivated by the scikit-learn ethos, of having powerful estimators that are straightforward to implement. Symbolic regression is a machine learning technique that aims to identify an underlying mathematical expression that best... -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
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Diems - CodeShine
Web application for posting, submitting, and evaluating assignments
CodeShine (a part of Di website) - is an application for posting, submitting, and evaluating assignments. As a whole, 'Di' is a shorthand for Deogiri Institute of Engineering and Management Studies, Aurangabad 431001, Maharashtra, India. -
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opsi
open source client management system, software deployment
opsi is a Client Management System for Windows and Linux clients based on Linux servers. opsi is used for automatic OS installation, software depolyment, hard- and software inventory, distributed software depots. -
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netconf-io
Very simple netconf RPC and notification support for python
In contrast to ncclient which uses threads and handles the bidirectional complexity internally this is a blocking non-bidirectiona implementation (meaning a single netconf connection can be used only for notification reception or one at a time RPC control). This usage limitation allows the netconf-io to be much simpler. -
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ANUGA is a software implementation of a hydrodynamic model which is specifically designed to model wetting and drying processes. ANUGA is a joint development project between Geoscience Australia (GA) and the Australian National University (ANU). ANUGA is now being developed on github at https://github.com/anuga-community/anuga_core For information on ANUGA please go to http://anuga.anu.edu.au The ANUGA project is described on http://en.wikipedia.org/wiki/ANUGA_Hydro
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YTD-Downloader
YTD-Downloader is a GUI-based Desktop Application.
YTD-Downloader is a GUI-based Desktop Application. Users can download audio and video from YouTube using this software. -
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m2cgen
Transform ML models into a native code
m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase... -
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Haircut_EQ
Fetches the historical Haircut data (%) of Equities and Gold Bonds
Haircut is the amount of margin money deducted while pledging the Equites/ Mutual Funds / Bonds for trading. A haircut value of 13% means that, if a share worth of Rs 100 is pledged for trading, then Rs. 13 will be deducted and Rs. 87 will be given as collateral margin for trading. It is based on previous closing price. This program is used to identify the real value of a share with date. It fetches the historical Haircut data (%) and Price of an equity listed in NSE, India at a... -
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Python-CDDB (PyCDDB) is a module written in Python to access a CDDB-server and get information about discs like: artist, disc-title, track titles and more.
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seladb/pickledb-rs
PickleDB-rs is a lightweight and simple key-value store
PickleDB-RS is a lightweight, fast, and key-value store written in Rust. Inspired by the Python PickleDB, it provides a simple, NoSQL database for small applications that require persistent key-value storage without the overhead of full-fledged databases. It is designed for speed and ease of use, with a JSON-based storage format. -
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The_Deck_Linux
Portable Penetration Testing Operating System
It is an Portable Penetration Testing Operating System designed for Beagle Bone AI. It is an debian based operating system fully packed with all latest Hacking Tools. The Root file system used in this Deck Linux is Ubuntu 20.04 LTS. It can be installed in Beagle Board AI and can use as a replacement for Laptop, Desktop. It can be placed on a drone too. It has a pre-installed MeshDeck (written by Philip Polstra) so it can be runned in a ZigBee network. We can attacks from up to a mile away... -
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CoffeeScript
Unfancy JavaScript
CoffeeScript is a lightweight programming language that compiles into JavaScript. It adds syntactic sugar inspired by Ruby, Python, and Haskell to improve brevity and readability, while producing predictable and efficient JavaScript output. Its design emphasizes that “It’s just JavaScript,” meaning any JS library works seamlessly, and compiled output is clean and performant. -
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Django REST Framework User
This Django User Model is customised user model
This Django User Model is a customized user model keeping in mind the practical need. JWT Support (Using Simple JWT) Mobile Number, single field for full name, REST API to register, REST API to login, MultiModelBackend: User can login using either of mobile, email or username. REST API to login with OTP (Same API endpoint as for OTP Verification; Set is_login: true while sending JSON request). OTP Verification for mobile and email, API to register / login with OTP (no pre-registration... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid.
