Showing 12 open source projects for "cli"

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  • Skillfully - The future of skills based hiring Icon
    Skillfully - The future of skills based hiring

    Realistic Workplace Simulations that Show Applicant Skills in Action

    Skillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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  • AestheticsPro Medical Spa Software Icon
    AestheticsPro Medical Spa Software

    Our new software release will dramatically improve your medspa business performance while enhancing the customer experience

    AestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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  • 1
    Video-subtitle-extractor

    Video-subtitle-extractor

    A GUI tool for extracting hard-coded subtitle (hardsub) from videos

    ...Use local OCR recognition, no need to set up and call any API, and do not need to access online OCR services such as Baidu and Ali to complete text recognition locally. Support GPU acceleration, after GPU acceleration, you can get higher accuracy and faster extraction speed. (CLI version) No need for users to manually set the subtitle area, the project automatically detects the subtitle area through the text detection model. Filter the text in the non-subtitle area and remove the watermark (station logo) text.
    Downloads: 75 This Week
    Last Update:
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  • 2
    CML

    CML

    Continuous Machine Learning | CI/CD for ML

    Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request.
    Downloads: 0 This Week
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  • 3
    dstack

    dstack

    Open-source tool designed to enhance the efficiency of workloads

    dstack is an open-source tool designed to enhance the efficiency of running ML workloads in any cloud (AWS, GCP, Azure, Lambda, etc). It streamlines development and deployment, reduces cloud costs, and frees users from vendor lock-in.
    Downloads: 0 This Week
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  • 4
    Metarank

    Metarank

    A low code Machine Learning service that personalizes articles

    ...Ingest historical item listings, clicks and item metadata so Metarank can find hidden dependencies in the data using our simple JSON format.No Machine Learning experience is required, run our CLI tool with a set of features in a YAML configuration. Run Metarank API service, feed it with real-time events and receive a personalized ranking for your items that will boost conversion, click-through rate or any other business-critical metric you define.
    Downloads: 1 This Week
    Last Update:
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  • The Most Powerful Software Platform for EHSQ and ESG Management Icon
    The Most Powerful Software Platform for EHSQ and ESG Management

    Addresses the needs of small businesses and large global organizations with thousands of users in multiple locations.

    Choose from a complete set of software solutions across EHSQ that address all aspects of top performing Environmental, Health and Safety, and Quality management programs.
    Learn More
  • 5
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    ...ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that automates the process of building best performing models for your Machine Learning scenario. All you have to do is load your data, and AutoML takes care of the rest of the model building process. ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more.
    Downloads: 1 This Week
    Last Update:
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  • 6
    Sagify

    Sagify

    LLMs and Machine Learning done easily

    ...It abstracts the complexities involved in setting up and managing SageMaker resources, allowing developers to focus on building and fine-tuning models. Sagify provides a command-line interface (CLI) and supports various machine-learning frameworks, making it accessible for a wide range of users.
    Downloads: 0 This Week
    Last Update:
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  • 7
    Sockeye

    Sockeye

    Sequence-to-sequence framework, focused on Neural Machine Translation

    ...If MXNet 2.x is installed, Sockeye can run both with PyTorch or MXNet. All models trained with 2.3.x (using MXNet) can be converted to models running with PyTorch using the converter CLI (sockeye.mx_to_pt).
    Downloads: 0 This Week
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  • 8
    ModelFox

    ModelFox

    ModelFox makes it easy to train, deploy, and monitor ML models

    ...Learn about your models and monitor them in production from your browser. ModelFox makes it easy to train, deploy, and monitor machine learning models. You can install the modelfox CLI by either downloading the binary from the latest GitHub release or by building from source. Train a machine learning model by running modelfox train with the path to a CSV file and the name of the column you want to predict. The CLI automatically transforms your data into features, trains a number of linear and gradient boosted decision tree models to predict the target column, and writes the best model to a .modelfox file. ...
    Downloads: 6 This Week
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  • 9
    ML.NET Samples

    ML.NET Samples

    Samples for ML.NET, an open source and cross-platform machine learning

    ...We're working on simplifying ML.NET usage with additional technologies that automate the creation of the model for you so you don't need to write the code by yourself to train a model, you simply need to provide your datasets. The "best" model and the code for running it will be generated for you. The ML.NET CLI (command-line interface) is a tool you can run on any command prompt (Windows, Mac or Linux) for generating good quality ML.NET models based on training datasets you provide. In addition, it also generates sample C# code to run/score that model plus the C# code that was used to create/train it so you can research what algorithm and settings it is using.
    Downloads: 0 This Week
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  • Award-Winning Medical Office Software Designed for Your Specialty Icon
    Award-Winning Medical Office Software Designed for Your Specialty

    Succeed and scale your practice with cloud-based, data-backed, AI-powered healthcare software.

    RXNT is an ambulatory healthcare technology pioneer that empowers medical practices and healthcare organizations to succeed and scale through innovative, data-backed, AI-powered software.
    Learn More
  • 10
    Docker Machine

    Docker Machine

    Machine management for a container-centric world

    ...Using docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host. Point the Machine CLI at a running, managed host, and you can run docker commands directly on that host. For example, run docker-machine env default to point to a host called default, follow on-screen instructions to complete env setup, and run docker ps, docker run hello-world, and so forth. Machine was the only way to run Docker on Mac or Windows previous to Docker v1.12.
    Downloads: 0 This Week
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  • 11
    xLearn

    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...
    Downloads: 0 This Week
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  • 12
    TexLexAn is an open source text analyser for Linux, able to estimate the readability and reading time, to classify and summarize texts. It has some learning abilities and accepts html, doc, pdf, ppt, odt and txt documents. Written in C and Python.
    Downloads: 0 This Week
    Last Update:
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