Search Results for "python-kinterbasdb" - Page 19
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Showing 625 open source projects for "python-kinterbasdb"
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MLBox
MLBox is a powerful Automated Machine Learning python library
MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. -
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AES Everywhere
Cross Language AES 256 Encryption Library
AES Everywhere is Cross Language Encryption Library that provides the ability to encrypt and decrypt data using a single algorithm in different programming languages and on different platforms. This is an implementation of the AES algorithm, specifically CBC mode, with 256-bit key length and PKCS7 padding. It implements OpenSSL-compatible cryptography with randomly generated salt. -
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I3D models trained on Kinetics
Convolutional neural network model for video classification
Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with... -
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pytorch-examples
Simple examples to introduce PyTorch
The pytorch-examples project is a collection of concise and practical examples demonstrating how to use PyTorch for machine learning and deep learning tasks. It focuses on clarity and minimalism, providing small, self-contained scripts that illustrate key concepts such as neural network training, optimization, and data handling. The examples cover a range of topics including supervised learning, generative models, and reinforcement learning, making it a valuable resource for both beginners... -
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Climate Modeling Courseware
Interactive lecture notes and assignments in Jupyter notebook format
...The focus of the course is on the hands-on use of both simple and complex climate models to build an understanding of the processes that control the planetary energy budget. The course makes extensive use of Python code and the Jupyter notebook for reproducible, self-describing calculations and figures. This repository contains a collection of linked Jupyter notebooks with lecture notes, examples and assignments. All notebooks are self-describing. -
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pyCraft
Minecraft-client networking library in Python
Minecraft Python Client Library. This project aims to be a modern, Python3-compatible, well-documented library for communication with a Minecraft server. Although pyCraft is compatible any supported server, only a subset of all packets are currently decoded or encoded by the library: those necessary to remain connected to the server, those used for chat, and some others. -
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pytkapp
Python package for develop an SDI/MDI application and set of widgets.
=========== pytkapp =========== Python package for develop an application that provide multi-documents/single-document interface with using of tkinter library and set of additional tkinter widgets. See available demos: pytkapp/demo/run_ptaoptionsdemo.py - run GUI demo for option's container (available widgets, rules) pytkapp/demo/run_ptamdidemo.py - run demo of MDI application pytkapp/demo/run_ptasdidemo.py - run demo of SDI application pytkapp/demo/run_tkwbasicdemo.py - run demo of basic widgets pytkapp/demo/run_tkwtldemo.py - run demo of tablelist-based widgets pytkapp/demo/run_diademo.py - run demo for dialog widgets (selector, xmessage) Notes ========= 1) PyTkApp package was tested on python 2.7, 3.1 2) If you planning to use tablelist-based widgets then you need to download tcl Tablelist package from http://www.nemethi.de/ -
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backtrader
Python Backtesting library for trading strategies
backtrader is a Python framework for developing, backtesting, and running trading strategies. Its Cerebro engine coordinates strategies, data feeds, brokers, indicators, analyzers, and execution. Developers can combine multiple strategies, instruments, and timeframes while resampling or replaying market data. The framework includes a large indicator library, custom indicator support, analyzers, position sizing, commissions, and trading calendars. -
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AeroPython
Classical Aerodynamics of potential flow using Python
The AeroPython series of lessons is the core of a university course (Aerodynamics-Hydrodynamics, MAE-6226) by Prof. Lorena A. Barba at the George Washington University. The first version ran in Spring 2014 and these Jupyter Notebooks were prepared for that class, with assistance from Barba-group PhD student Olivier Mesnard. In Spring 2015, we revised and extended the collection, adding student assignments to strengthen the learning experience. The course is also supported by an open learning... -
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Tensor Algebra Compiler
The Tensor Algebra Compiler (taco) computes sparse tensor expressions
A fast and versatile compiler-based library for sparse linear and tensor algebra. TACO can be used to implement sparse linear and tensor algebra applications in a wide range of domains. TACO supports a wide range of sparse (and dense) linear/tensor algebra computations, from simpler ones like sparse matrix-vector multiplication to more complex ones like MTTKRP on higher-order sparse tensors. Tensors can be stored in a variety of storage formats, including commonly-used sparse matrix and... -
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Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This... -
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tkColorPicker
Color picker dialog for Tkinter, alternative to tkinter.colorchooser
The tkcolorpicker module contains a `ColorPicker` class which implements the color picker dialog and an `askcolor` function that displays the color picker and returns the chosen color in RGB and HTML formats. -
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data-science-ipython-notebooks
Data science Python notebooks: Deep learning
Data Science IPython Notebooks is a broad, curated set of Jupyter notebooks covering Python, data wrangling, visualization, machine learning, deep learning, and big data tools. It aims to be a practical map of the ecosystem, showing hands-on examples with libraries such as NumPy, pandas, matplotlib, scikit-learn, and others. Many notebooks introduce concepts step by step, then apply them to real datasets so readers can see techniques in action. -
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MITIE
MITIE: library and tools for information extraction
...MITIE offers several pre-trained models providing varying levels of support for both English, Spanish, and German trained using a variety of linguistic resources (e.g., CoNLL 2003, ACE, Wikipedia, Freebase, and Gigaword). The core MITIE software is written in C++, but bindings for several other software languages including Python, R, Java, C, and MATLAB allow a user to quickly integrate MITIE into his/her own applications. -
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numpy_exercises
Numpy exercises
numpy_exercises is a collection of short practice problems designed to teach numerical computing through individual NumPy functions. The material is organized as Jupyter notebooks so learners can work interactively and compare their answers with companion solution notebooks. Exercises cover array creation, manipulation, string operations, help utilities, input and output, and linear algebra. Additional sections address discrete Fourier transforms, logic functions, mathematics, random... -
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CFD Python
Sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. -
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Maya
Datetimes for Humans
Maya is a Python library that simplifies working with datetime objects. It provides a human-friendly API for parsing, formatting, and manipulating dates and times, addressing common frustrations with Python's built-in datetime module. -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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PlotNeuralNet
Latex code for making neural networks diagrams
Latex code for drawing neural networks for reports and presentations. Have a look into examples to see how they are made. Additionally, let's consolidate any improvements that you make and fix any bugs to help more people with this code. -
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ComplexEventExtraction
Expression pattern collection of Chinese compound event extraction
ComplexEventExtraction is a Chinese NLP project for identifying relationships between events expressed in compound sentences. It defines patterns for causal, conditional, sequential, contrastive, and parallel event structures. The system uses explicit connective words and phrase combinations to split text into linked event pairs. Extracted results can support event graphs that represent how situations develop, conflict, or depend on one another. The repository catalogs hundreds of linguistic... -
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Autologging
Easier logging and tracing of Python functions and class methods.
..."autologging.traced" decorates a class to provide automatic CALL/RETURN tracing for all class, static, and instance methods, as well as the special __init__ method (by default) "autologging.TRACE" is a custom log level (lower than logging.DEBUG) that is registered with the Python logging module when autologging is imported -
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Teach Me Quantum
Practical Course on Quantum Information Science and Quantum Computing
A university-level course on Quantum Computing and Quantum Information Science that incorporates IBM Q Experience and Qiskit. This course is adequate for general audiences without prior knowledge on Quantum Mechanics and Quantum Computing (see prior knowledge), has an estimated average duration of 10 weeks at 3h/week (see duration), and is meant to be the entrypoint into the Quantum World. -
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WIP
Create Siri Shortcuts with Python
python-shortcuts is a library to create Siri Shortcuts on your laptop with your favorite text editor. It uses toml to represent shortcuts. The library is in a very early development state (PR welcome!), so it does not support all actions from the Shortcuts app. -
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Functional, Data Science Intro To Python
[tutorial]A functional, Data Science focused introduction to Python
The first section is an intentionally brief, functional, data science-centric introduction to Python. The assumption is a someone with zero experience in programming can follow this tutorial and learn Python with the smallest amount of information possible. The sections after that, involve varying levels of difficulty and cover topics as diverse as Machine Learning, Linear Optimization, build systems, command line tools, recommendation engines, Sentiment Analysis and Cloud Computing. -
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Skater
Python library for model interpretation/explanations
Skater is a unified framework to enable Model Interpretation for all forms of the model to help one build an Interpretable machine learning system often needed for real-world use-cases(** we are actively working towards to enabling faithful interpretability for all forms models). It is an open-source python library designed to demystify the learned structures of a black box model both globally(inference on the basis of a complete data set) and locally(inference about an individual prediction). The concept of model interpretability in the field of machine learning is still new, largely subjective, and, at times, controversial. Model interpretation is the ability to explain and validate the decisions of a predictive model to enable fairness, accountability, and transparency in algorithmic decision-making. ...
