Exploring Open-Source Alternatives to Landing AI for Robust MLOps

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • deepdetect

    Deep Learning API and Server in C++14 support for Caffe, PyTorch,TensorRT, Dlib, NCNN, Tensorflow, XGBoost and TSNE

    For those seeking a lightweight solution for setting up deep learning REST APIs across platforms without the complexity of Kubernetes, Deepdetect is worth considering.

  • awesome-production-machine-learning

    A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

    One trove of treasures is the awesome-production-machine-learning repository on GitHub. This curated list provides a multitude of frameworks, libraries, and software designed to facilitate various stages of the ML lifecycle.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  • scikit-image

    Image processing in Python

    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

  • ultralytics

    NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite

    When browsing the state-of-the-art in object detection on Papers with Code, I found the YOLO model to be one of the most popular, accurate, and fastest. That being said, I would recommend having a look at Ultralytics, which provides the tools to evaluate, predict, and export the latest versions of YOLO models with only a few lines of code.

  • datasets

    A collection of free datasets hosted with ReductStore (by reductstore)

    When seeking an on-premise alternative to LandingEdge for sophisticated edge computing and computer vision tasks, ReductStore emerges as a compelling solution. This Time-Series Database is tailored for Blob Data, emphasizing optimizations that cater to the unique demands of Edge Computing, IoT, and Computer Vision applications.

  • anomalib

    An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

    Then, when it comes to semi-supervised learning for anomaly detection, I had positive experiences with Anomalib which offers a robust library dedicated to deep learning anomaly detection algorithms. They implemented the latest models with PyTorch and offer tools to benchmark their performance.

  • Pandas

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  • coco-annotator

    :pencil2: Web-based image segmentation tool for object detection, localization, and keypoints

    For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.

  • OpenCV

    Open Source Computer Vision Library

    Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

  • label-studio

    Label Studio is a multi-type data labeling and annotation tool with standardized output format

    For instance, the COCO Annotator is a web-based image annotation tool tailored for the COCO dataset format, allowing collaborative labeling with features like attribute tagging and automatic segmentation. Similarly, Label Studio offers an easy-to-use interface for bounding box object labeling in images.

  • nuclio

    High-Performance Serverless event and data processing platform

    For the efficiency of "serverless" functions, I would consider Nuclio as a viable option to rely on.

  • cvat

    Discontinued Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

    Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision.

  • netron

    Visualizer for neural network, deep learning and machine learning models

    In exploring open-source projects, I've come across several promising tools capable of managing deep-learning models for images. Significantly, tools such as NETRON provide visualization of neural networks, while SHAP can be used for evaluating the significance of outputs.

  • MLflow

    Open source platform for the machine learning lifecycle

    Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.

  • pachyderm

    Data-Centric Pipelines and Data Versioning

    Pachyderm specializes in creating compliance-focused pipelines that integrate with enterprise-level storage solutions.

  • alibi-detect

    Algorithms for outlier, adversarial and drift detection

    Numerous tools exist for detecting anomalies in time series data, but Alibi Detect stood out to me, particularly for its capabilities and its compatibility with both TensorFlow and PyTorch backends.

  • dvc

    🦉 ML Experiments and Data Management with Git

    Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.

  • clearml-helm-charts

    Helm chart repository for the new unified way to deploy ClearML on Kubernetes. ClearML - Auto-Magical CI/CD to streamline your AI workload. Experiment Management, Data Management, Pipeline, Orchestration, Scheduling & Serving in one MLOps/LLMOps solution

    On another front, ClearML excels at automating the monitoring and graphic representation of models while facilitating training tasks remotely.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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