Search Results for "python user interface" - Page 4
Sort By:
Showing 117 open source projects for "python user interface"
View related business solutions-
Resolve Support Tickets 2x Faster with ServoDeskWhat if You Could Automate 90% of Your Repetitive Tasks in Under 30 Days? At ServoDesk, we help businesses like yours automate operations with AI, allowing you to cut service times in half and increase productivity by 25% - without hiring more staff.
-
Rent Manager SoftwareRent Manager is award-winning property management software built for residential, commercial, and short-term-stay portfolios of any size. The program’s fully customizable features include a double-entry accounting system, maintenance management/scheduling, marketing integration, mobile applications, more than 450 insightful reports, and an API that integrates with the best PropTech providers on the market.
-
1
Opyrator
Turns your machine learning code into microservices with web API
...It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python function. An Opyrator-compatible function is required to have an input parameter and return value based on Pydantic models. The input and output models are specified via type hints. You can launch a graphical user interface - powered by Streamlit - for your compatible function. -
2
Couler
Unified Interface for Constructing and Managing Workflows
Couler is a system designed for unified machine learning workflow optimization in the cloud. Couler endeavors to provide a unified interface for constructing and optimizing workflows across various workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow. Couler enhances workflow efficiency through features like Autonomous Workflow Construction, Automatic Artifact Caching Mechanisms, Big Workflow Auto Parallelism Optimization, and Automatic Hyperparameters Tuning. -
3
Keepsake
Version control for machine learning
Keepsake is a Python library that uploads files and metadata (like hyperparameters) to Amazon S3 or Google Cloud Storage. You can get the data back out using the command-line interface or a notebook. -
4
Ceka
Crowd Environment and its Knowledge Analysis
A knowledge analysis tool for crowdsourcing based on Weka. We also have a Python version of Crowdsourcing Learning: CrowdwiseKit on GitHub (https://github.com/tssai-lab/CrowdwiseKit). -
Lightspeed golf course management softwareFrom tee sheet management, point of sale and payment processing to marketing, automation, reporting and more—Lightspeed is built for the pro shop, restaurant, back office, beverage cart and beyond.
-
5
Turi Create
Simplifies the development of custom machine learning models
...If you want your app to recognize specific objects in images, you can build your own model with just a few lines of code. Turi Create supports macOS 10.12+, Linux (with glibc 2.10+), Windows 10 (via WSL). Turi Create requires Python 2.7, 3.5, 3.6, 3.7, 3.8. Also, x86_64 architecture, and at least 4 GB of RAM. We recommend using virtualenv to use, install, or build Turi Create. The package User Guide and API Docs contain more details on how to use Turi Create. If you want to build Turi Create from source, see BUILD.md. Turi Create does not require a GPU, but certain models can be accelerated 9-13x by utilizing a GPU. -
6
Spectral Python
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more. -
7
StellarGraph
Machine Learning on Graphs
...StellarGraph supports the analysis of many kinds of graphs. StellarGraph is built on TensorFlow 2 and its Keras high-level API, as well as Pandas and NumPy. It is thus user-friendly, modular and extensible. It interoperates smoothly with code that builds on these, such as the standard Keras layers and scikit-learn. -
8
cintruder
CIntruder - OCR Bruteforcing Toolkit
Captcha Intruder is an automatic pentesting tool to bypass captchas. -> CIntruder-v0.4 (.zip) -> md5 = 6326ab514e329e4ccd5e1533d5d53967 -> CIntruder-v0.4 (.tar.gz) ->md5 = 2256fccac505064f3b84ee2c43921a68 -------------------------------------------- -
9
COCO Annotator
Web-based image segmentation tool for object detection & localization
COCO Annotator is a web-based image annotation tool designed for versatility and efficiently label images to create training data for image localization and object detection. It provides many distinct features including the ability to label an image segment (or part of a segment), track object instances, label objects with disconnected visible parts, and efficiently store and export annotations in the well-known COCO format. The annotation process is delivered through an intuitive and... -
Easy-to-use Business Software for the Waste Management Software IndustryDOP Software’s mission is to streamline waste and recycling business’ processes by providing them with dynamic, comprehensive software and services that increase productivity and quality of performance.
-
10
ModelDB
Open Source ML Model Versioning, Metadata, and Experiment Management
An open-source system for Machine Learning model versioning, metadata, and experiment management. ModelDB is an open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle. -
11
SINGA
A distributed deep learning platform
Apache SINGA is an Apache Top Level Project, focusing on distributed training of deep learning and machine learning models. Various example deep learning models are provided in SINGA repo on Github and on Google Colab. SINGA supports data parallel training across multiple GPUs (on a single node or across different nodes). SINGA supports various popular optimizers including stochastic gradient descent with momentum, Adam, RMSProp, and AdaGrad, etc. SINGA records the computation graph and... -
12
ChainerRL
ChainerRL is a deep reinforcement learning library
...Environments that support the subset of OpenAI Gym's interface (reset and step methods) can be used. -
13
imgaug
Image augmentation for machine learning experiments
imgaug is a library for image augmentation in machine learning experiments. It supports a wide range of augmentation techniques, allows to easily combine these and to execute them in random order or on multiple CPU cores, has a simple yet powerful stochastic interface and can not only augment images but also key points/landmarks, bounding boxes, heatmaps and segmentation maps. Affine transformations, perspective transformations, contrast changes, gaussian noise, dropout of regions,... -
14
Phenalysis
Analyze agronomic plant research plots in aerial orthomosaic images.
A graphical user interface to import, analyze and export plots from orthomosaic images of agronomic trials. Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on Wheat in a Hot and Dry Climate. ... -
15
Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
...The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a minimal version of Anaconda) and several Python packages installed. The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the Git BASH terminal. JupyterLab has a built-in selectable dark theme, so you only need to install something if you want to use the classic notebook interface. -
16
Spotlight
Deep recommender models using PyTorch
Spotlight uses PyTorch to build both deep and shallow recommender models. By providing both a slew of building blocks for loss functions (various pointwise and pairwise ranking losses), representations (shallow factorization representations, deep sequence models), and utilities for fetching (or generating) recommendation datasets, it aims to be a tool for rapid exploration and prototyping of new recommender models. Spotlight offers a slew of popular datasets, including Movielens 100K, 1M,... -
17
xLearn
High performance, easy-to-use, and scalable machine learning (ML)
xLearn is a high-performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM), all of which can be used to solve large-scale machine learning problems. xLearn is especially useful for solving machine learning problems on large-scale sparse data. Many real-world datasets deal with high dimensional sparse feature vectors like a recommendation system where the number of categories and... -
18
NeuralCoref
Fast Coreference Resolution in spaCy with Neural Networks
...NeuralCoref is production-ready, integrated in spaCy's NLP pipeline and extensible to new training datasets. For a brief introduction to coreference resolution and NeuralCoref, please refer to our blog post. NeuralCoref is written in Python/Cython and comes with a pre-trained statistical model for English only. NeuralCoref is accompanied by a visualization client NeuralCoref-Viz, a web interface powered by a REST server that can be tried online. -
19
automl-gs
Provide an input CSV and a target field to predict, generate a model
Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see exactly how the data is processed, and how the model is constructed, and you can make tweaks as necessary. automl-gs is an AutoML tool which, unlike Microsoft's NNI, Uber's Ludwig, and TPOT, offers a zero code/model definition interface to getting an optimized model and data transformation pipeline in multiple popular ML/DL frameworks, with minimal Python dependencies (pandas + scikit-learn + your framework of choice). automl-gs is designed for citizen data scientists and engineers without a deep statistical background under the philosophy that you don't need to know any modern data preprocessing and machine learning engineering techniques to create a powerful prediction workflow. -
20
Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
Tensorpack is a neural network training interface based on TensorFlow v1. Uses TensorFlow in the efficient way with no extra overhead. On common CNNs, it runs training 1.2~5x faster than the equivalent Keras code. Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. -
21
TensorImage
Image classification library for easily training and deploying models
(Visit our github repository at https://github.com/TensorImage/tensorimage for more information) TensorImage is and open source package for image classification. It has a wide range of data augmentation operations that can be performed over training data to prevent overfitting and increase testing accuracy. TensorImage is easy to use and manage as all files, trained models and data are organized within a workspace directory, which you can change at any time in the configuration file,... -
22
fscaret_shiny
UI for fscaret
User Interface (ui) application which implements the automated feature selection provided by the 'fscaret' package of R-environment. -
23
AI-Blocks
A powerful and intuitive WYSIWYG to create Machine Learning models
A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models! The concept of AI-Blocs is to have a simple scene with draggable objects that have scripts attached to them. The model can be run directly on the editor or be exported to a standalone script that runs on Tensorflow. Variables are parsed from python scripts and can be edited from the AI-Blocs properties panel. -
24
Lip Reading
Cross Audio-Visual Recognition using 3D Architectures
The input pipeline must be prepared by the users. This code is aimed to provide the implementation for Coupled 3D Convolutional Neural Networks for audio-visual matching. Lip-reading can be a specific application for this work. Audio-visual recognition (AVR) has been considered as a solution for speech recognition tasks when the audio is corrupted, as well as a visual recognition method used for speaker verification in multi-speaker scenarios. The approach of AVR systems is to leverage the... -
25
Machine Learning framework in Python
