Search Results for "qgis-osgeo4w-2.6.1-1-setup" - Page 8
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Showing 2896 open source projects for "qgis-osgeo4w-2.6.1-1-setup"
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Diffgram
Training data (data labeling, annotation, workflow) for all data types
From ingesting data to exploring it, annotating it, and managing workflows. Diffgram is a single application that will improve your data labeling and bring all aspects of training data under a single roof. Diffgram is world’s first truly open source training data platform that focuses on giving its users an unlimited experience. This is aimed to reduce your data labeling bills and increase your Training Data Quality. Training Data is the art of supervising machines through data. This... -
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AWS EC2 Instance Connect CLI
All-in-one client for EC2 Instance Connect that handles key brokerage
This is an all-in-one client for EC2 Instance Connect that handles key brokerage and establishing connections to EC2 Instances through an interface near-identical to standard system ssh, sftp, and other utilities. This is a Python client for accessing EC2 instances via AWS EC2 Instance Connect. This module supports Python 2.7.x and 3+. This package is available on PyPI for pip installation, ie, pip install ec2instanceconnectcli. It is strongly encouraged you set up a virtual environment... -
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bidict
The bidirectional mapping library for Python
... across all supported Python versions. Enterprise-level support for bidict can be obtained via the Tidelift subscription. One of the best things about bidict is that it touches a surprising number of interesting Python corners, especially given its small size and scope. Choose a tier and GitHub handles everything else. Your GitHub sponsorship will automatically go on the same bill you already have set up with GitHub, so after the one-click signup, there’s nothing else to do. -
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zvt
Modular quant framework
.... The core concept of the system is visual, and the name of the interface corresponds to it one-to-one, so it is also uniform and extensible. You can write and run the strategy in your favorite ide, and then view its related targets, factor, signal and performance on the UI. Once you are familiar with the core concepts of the system, you can apply it to any target in the market. -
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Pipenv
Python Development Workflow for Humans
Pipenv is a package manager that brings all the best of the packaging world together to the Python world. It's got everything you could need: bundler, composer, npm, cargo, yarn and more all in one convenient package so you can easily set up a working environment. Pipenv creates and manages a virtualenv automatically, and can add or remove packages from your Pipfile as you install/uninstall packages. It also produces the Pipfile.lock, which is essential for deterministic builds. Pipenv... -
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NeoDB
NeoDB is a self-hosted server tracking what you read/watch/listen/play
NeoDB is an open-source software and global community platform since 2021. It helps users to manage and explore collections, reviews, and ratings for various cultural products, including books, movies, music, podcasts, games, and performances. Additionally, users can share their collections, publish microblogs, and engage with others in the Fediverse. NeoDB integrates the functionalities of platforms like Goodreads, Letterboxd, RateYourMusic, and Podchaser, among others. It also supports... -
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Vorta Backup Client
Desktop Backup Client for Borg Backup
Vorta is a backup client for macOS and Linux desktops. It integrates the mighty Borg Backup with your favorite desktop environment to protect your data from disk failure, ransomware and theft. -
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KerasTuner
A Hyperparameter Tuning Library for Keras
KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily configure your search space with a define-by-run syntax, then leverage one of the available search algorithms to find the best hyperparameter values for your models. KerasTuner comes with Bayesian Optimization, Hyperband, and Random Search algorithms built-in, and is also designed to be easy for researchers to extend in order to experiment with new search... -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution, Bayesian... -
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EconML
Python Package for ML-Based Heterogeneous Treatment Effects Estimation
EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal of combining state-of-the-art machine learning techniques with econometrics to bring automation to complex causal inference problems. One of the biggest promises of machine learning is to automate decision-making in a multitude of domains. At the core of many data-driven... -
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Flower
Flower: A Friendly Federated Learning Framework
A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state... -
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sktime
A unified framework for machine learning with time series
... interface for distinct but related time series learning tasks. It features dedicated time series algorithms and tools for composite model building such as pipelining, ensembling, tuning, and reduction, empowering users to apply an algorithm designed for one task to another. -
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Portainer Templates
500+ 1-click Portainer app templates
A compiled list of 500+ ready-to-go Portainer App templates. In Portainer, App Templates enable you to easily deploy services with a predetermined configuration, while allowing you to customize options through the web UI. While Portainer ships with some default templates, it's often helpful to have 1-click access to many more apps + stacks, without having to constantly switch template sources. This repo combines app templates from several sources, to create a ready-to-go template file... -
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DeepH-pack
Deep neural networks for density functional theory Hamiltonian
DeepH-pack is the official implementation of the DeepH (Deep Hamiltonian) method described in the paper Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation and in the Research Briefing. DeepH-pack supports DFT results made by ABACUS, OpenMX, FHI-aims or SIESTA and will support HONPAS. -
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borb
borb is a library for reading, creating and manipulating PDF files
borb is a library for creating and manipulating PDF files in python. borb is a pure python library to read, write, and manipulate PDF documents. It represents a PDF document as a JSON-like data structure of nested lists, dictionaries and primitives (numbers, string, booleans, etc) This is currently a one-man project, so the focus will always be to support those use-cases that are more common in favor of those that are rare. -
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pikepdf
A Python library for reading and writing PDF, powered by QPDF
pikepdf is a Python library allowing the creation, manipulation, and repair of PDFs. It provides a Pythonic wrapper around the C++ PDF content transformation library, QPDF. Python + QPDF = “py” + “qpdf” = “pyqpdf”, which looks like a dyslexia test and is no fun to type. But say “pyqpdf” out loud, and it sounds like “pikepdf”. pikepdf is a library intended for developers who want to create, manipulate, parse, repair, and abuse the PDF format. It supports reading and write PDFs, including... -
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OpenLLM
Operating LLMs in production
An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. With OpenLLM, you can run inference with any open-source large-language models, deploy to the cloud or on-premises, and build powerful AI apps. Built-in supports a wide range of open-source LLMs and model runtime, including Llama 2， StableLM, Falcon, Dolly, Flan-T5, ChatGLM, StarCoder, and more. Serve LLMs over RESTful API or gRPC with one command, query via WebUI... -
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ydata-profiling
Create HTML profiling reports from pandas DataFrame objects
ydata-profiling primary goal is to provide a one-line Exploratory Data Analysis (EDA) experience in a consistent and fast solution. Like pandas df.describe() function, that is so handy, ydata-profiling delivers an extended analysis of a DataFrame while allowing the data analysis to be exported in different formats such as html and json. -
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Recap
Recap tracks and transform schemas across your whole application
Recap is a schema language and multi-language toolkit to track and transform schemas across your whole application. Your data passes through web services, databases, message brokers, and object stores. Recap describes these schemas in a single language, regardless of which system your data passes through. Recap schemas can be defined in YAML, TOML, JSON, XML, or any other compatible language. -
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Tributary
Streaming reactive and dataflow graphs in Python
Tributary is a library for constructing dataflow graphs in Python. Unlike many other DAG libraries in Python (airflow, luigi, prefect, dagster, dask, kedro, etc), tributary is not designed with data/etl pipelines or scheduling in mind. Instead, tributary is more similar to libraries like mdf, loman, pyungo, streamz, or pyfunctional, in that it is designed to be used as the implementation for a data model. One such example is the greeks library, which leverages tributary to build data models... -
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web.py
Web framework for python that is as simple as it is powerful
web.py is a web framework for Python that is as simple as it is powerful. web.py is in the public domain, you can use it for whatever purpose with absolutely no restrictions. web.py was originally published while Aaron Swartz worked at reddit.com, where the site used it as it grew to become one of the top 1000 sites according to Alexa and served millions of daily page views. “It’s the anti-framework framework. web.py doesn’t get in your way,” explained founder Steve Huffman. (The site... -
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Typer
Typer, build great CLIs, based on Python type hints
... of code to your app: 1 import, 1 function call. Grow in complexity as much as you want, create arbitrarily complex trees of commands and groups of subcommands, with options and arguments. And it's intended to be the FastAPI of CLIs. Typer stands on the shoulders of a giant. Its only internal dependency is Click. -
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
... of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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Prompt Declaration Language
Prompt Declaration Language is a declarative prompt programming lang
LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming... -
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Streamline Analyst
AI agent that streamlines the entire process of data analysis
Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates all the tasks such as data cleaning, preprocessing, and even complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless.