Alternatives to Amazon SageMaker Ground Truth

The training data platform for AI teams. A machine learning model can only be as good as the training data it uses. Labelbox is an integrated platform that allows you to create and manage high quality training data in one place. It also supports your production pipeline with powerful APIs. A powerful image labeling tool for segmentation, object detection, and image classification. You need precise and intuitive image segmentation tools when every pixel is important. You can customize the tools to suit your particular use case, including custom attributes and more. The performant video labeling editor is for cutting-edge computer visual. Label directly on the video at 30 FPS, with frame level. Labelbox also provides per-frame analytics that allow you to create faster models. It's never been easier to create training data for natural language intelligence. You can quickly and easily label text strings, conversations, paragraphs, or documents with fast and customizable classification.

Data platform for vision AI that is enterprise-grade. Dataloop is an all-in-one solution for building and deploying powerful computer-vision pipelines. It automates data ops, data labeling, data ops, customizing data pipelines, and weaving the human-inthe-loop for data validation. Our vision is to make machine-learning-based systems affordable, accessible, and scalable for everyone.

Ango Hub is an all-in-one, quality-oriented data annotation platform that AI teams can use. Ango Hub is available on-premise and in the cloud. It allows AI teams and their data annotation workforces to quickly and efficiently annotate their data without compromising quality. Ango Hub is the only data annotation platform that focuses on quality. It features features that enhance the quality of your annotations. These include a centralized labeling system, a real time issue system, review workflows and sample label libraries. There is also consensus up to 30 on the same asset. Ango Hub is versatile as well. It supports all data types that your team might require, including image, audio, text and native PDF. There are nearly twenty different labeling tools that you can use to annotate data. Some of these tools are unique to Ango hub, such as rotated bounding box, unlimited conditional questions, label relations and table-based labels for more complicated labeling tasks.

Amazon SageMaker, a fully managed service, provides data scientists and developers with the ability to quickly build, train, deploy, and deploy machine-learning (ML) models. SageMaker takes the hard work out of each step in the machine learning process, making it easier to create high-quality models. Traditional ML development can be complex, costly, and iterative. This is made worse by the lack of integrated tools to support the entire machine learning workflow. It is tedious and error-prone to combine tools and workflows. SageMaker solves the problem by combining all components needed for machine learning into a single toolset. This allows models to be produced faster and with less effort. Amazon SageMaker Studio is a web-based visual interface that allows you to perform all ML development tasks. SageMaker Studio allows you to have complete control over each step and gives you visibility.

Appen combines the intelligence of over one million people around the world with cutting-edge algorithms to create the best training data for your ML projects. Upload your data to our platform, and we will provide all the annotations and labels necessary to create ground truth for your models. An accurate annotation of data is essential for any AI/ML model to be trained. This is how your model will make the right judgments. Our platform combines human intelligence with cutting-edge models to annotation all types of raw data. This includes text, video, images, audio and video. It creates the exact ground truth for your models. Our user interface is easy to use, and you can also programmatically via our API.

Amazon Augmented AI (Amazon A2I), makes it easy to create the workflows needed for human review of ML prediction. Amazon A2I provides human review for all developers. This removes the undifferentiated work involved in building systems that require human review or managing large numbers. Machine learning applications often require humans to review low confidence predictions in order to verify that the results are accurate. In some cases, such as extracting information from scanned mortgage applications forms, human review may be required due to poor scan quality or handwriting. However, building human review systems can be costly and time-consuming because it involves complex processes or "workflows", creating custom software to manage review tasks, results, and managing large numbers of reviewers.

Our proprietary labeling platform allows us to label your data with higher quality standards in order to meet the requirements of complex AI projects. Now you can create the products that your customers love.

A class-agnostic, pixel-perfect automated annotation platform. Built for teams that have a lot of data and strict quality requirements but little time. Ground truth creation can be scaled up 10x. Collaborate with unlimited team members, annotators and seamlessly integrate into your deep learning pipeline. Create ground truth 10x faster with pixel-perfect annotations. Use V7's intuitive tools for labeling data and automating your ML pipelines. The ultimate image and Video Annotation Solution

Our AI Training Data Platform combines the best of data annotators and computer vision capabilities, with the power of the AI Community of professional annotations. GT Manage: Our proprietary platform manager for our 1M+ community. GT Annotate is our proprietary data annotation software. GT Data: Our global expertise for data collection and creation. Human-powered AI is the foundation of all AI. Our fully automated platform allows sophisticated data annotation across data types, all within the same software. It also provides seamless project and AI Community Management. Ground Truth (GT Annotate) is our proprietary software for data annotation. It was carefully designed to allow teams to create quality AI training datasets quickly and accurately. Below are some examples of how the technology is used.

The most flexible data annotation software. Quickly installable. Create custom UIs, or use pre-built labeling template. Layouts and templates that can be customized to fit your dataset and workflow. Detect objects in images. Supported are boxes, polygons and key points. Partition an image into multiple segments. Use ML models to optimize and pre-label the process. Webhooks, Python SDK and API allow you authenticate, create tasks, import projects, manage model predictions and more. ML backend integration allows you to save time by using predictions as a tool for your labeling process. Connect to cloud object storage directly and label data there with S3 and GCP. Data Manager allows you to manage and prepare your datasets using advanced filters. Support multiple projects, use-cases, and data types on one platform. You can preview the labeling interface as you type in the configuration. You can see live serialization updates at the bottom of the page.

The best platform for the entire lifecycle of computer vision. You can go from image annotation to precise neural networks in 10x less time. Our best-in-class data labeling software transforms images, videos, and 3D point clouds into high-quality training data. You can train your models, track experiments and visualize the results. Our self-hosted solution guarantees data privacy, powerful customization capabilities and easy integration into any technology stack. Computer Vision is a turnkey solution: multi-format data management, quality control at scale, and neural network training in an end-to-end platform. Professional video editing software created by data scientists for data science -- the most powerful tool for machine learning and other purposes.

A powerful labeling platform for all stages and types of ML development. We leverage a suite of industry-leading computer vision algorithms to automatically detect and classify the content of your images and videos. Creating detailed segmentation information is a time-consuming process. Machine assistance speeds up task completion by as much as 70%, saving you both time and money. We leverage ML to propose labels that accelerate human labeling. This includes computer vision models to automatically detect, localize, and classify entities in your images and videos before handing off the task to our workforce. Automatic labelling reduces workforce costs and allows annotators to spend their time on the more complicated steps of the annotation process. Our video annotation tool is built to handle 4K resolution and long-running videos natively and provides innovative features like interpolation, object proposal, and entity resolution.

Mindkosh is your premier data management platform, streamlining the curation, tagging, and verification of datasets for AI initiatives. Our top-tier data annotation platform merges team-oriented functionalities with AI-enhanced annotation tools, delivering an all-encompassing toolkit for categorizing diverse data types, including images, videos, and 3D point clouds from Lidar. For images, Mindkosh offers advanced semi-automated segmentation, pre-labeling of bounding boxes, and completely automatic OCR capabilities. For video annotation, Mindkosh's automated interpolation significantly reduces the need for manual labeling. And for Lidar data, single-click annotation enables swift cuboid generation with just one click. If you are simply looking to get your data labeled, our high quality data annotation services combined with an easy to use Python SDK and web-based review platform, provide an unmatched experience.

The platform is easy to use and quick to implement machine learning and computer vision workflows. Sense makes it easy to create and deploy AI IoT solutions on any cloud, edge or on-premise. Learn how Sense makes it easy for AI/ML teams to create and deploy AI IoT solutions to any cloud, the edge or on-premise. It is powerful enough for ML engineers but simple enough for subject matter experts. Sense Data Annotation maximizes the success of your machine-learning models by making it the easiest and fastest way to label image and video data for high-quality training datasets. The Sense platform provides one-touch labeling integration to enable continuous machine learning at edge for simplified management.

Automaton AI's Automaton AI's DNN model and training data management tool, ADVIT, allows you to create, manage, and maintain high-quality models and training data in one place. Automated optimization of data and preparation for each stage of the computer vision pipeline. Automate data labeling and streamline data pipelines in house Automate the management of structured and unstructured video/image/text data and perform automated functions to refine your data before each step in the deep learning pipeline. You can train your own model with accurate data labeling and quality assurance. DNN training requires hyperparameter tuning such as batch size, learning rate, and so on. To improve accuracy, optimize and transfer the learning from trained models. After training, the model can be put into production. ADVIT also does model versioning. Run-time can track model development and accuracy parameters. A pre-trained DNN model can be used to increase the accuracy of your model for auto-labeling.

We make data for the world's most valuable companies. Innodata solves your most difficult data engineering problems using artificial intelligence and human expertise. Innodata offers the services and solutions that you need to harness digital information at scale and drive digital disruption within your industry. We secure and efficiently collect and label sensitive data. This provides ground truth that is close to 100% for AI and ML models. Our API is simple to use and ingests unstructured data, such as contracts and medical records, and generates structured XML that conforms to schemas for downstream applications and analytics. We make sure that mission-critical databases are always accurate and up-to-date.

The best data will help you achieve peak model performance. Create and manage training data for any visual modality. Debug models, boost performance and make foundation models yours. Expert review, QA, and QC workflows will help you deliver better datasets to your artificial-intelligence teams, improving model performance. Encord's Python SDK allows you to connect your data and models, and create pipelines that automate the training of ML models. Improve model accuracy by identifying biases and errors in your data, labels, and models.

Our fully managed solution makes it easy to create training datasets for computer-vision models. Data labeling is a key factor in creating effective deep learning models. We aim to be the industry's most trusted data labeling platform, helping companies fully take advantage of AI's potential. You can organize your media using discrete categories. You can identify items of interest using one or more bounding boxes. Similar to bounding boxes but with more precision. You can annotate objects with precise width, depth, height. Each pixel in an image should be classified. Each point in an image should be marked. Annotate straight lines within an image. Measure, yaw and pitch the item of interest. Annotate timestamps in audio and video content. Annotate lines that are not defined in an image.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for building better, faster and stronger AI. We help enterprises and public sector organizations transform their data into actionable insights. Our technology is used across many industries including Defense, Retail, Manufacturing, Media and Entertainment, and more. We help our customers create innovative AI solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been a market leader in computer vision AI since winning the top five places in image classification at the 2013 ImageNet Challenge. Clarifai is headquartered in Delaware

We offer the highest quality SLA (>95%) even for the most complicated workflows. Our team can assist with everything from the implementation of a solid quality rubric to raising edge case. We are an ethical AI company that has provided economic opportunities to over 52,000 people in underserved and marginalized areas. ML Assisted annotation allowed for efficiency improvements of up to 3-4x per class annotation. We are able to quickly adapt to ramp-ups and focus shifts. Secure work environments are ensured by ISO-certified delivery centers, biometric authentication, 2FA user authentication, and ISO-certified delivery centers. You can quickly re-prioritize tasks, give quality feedback, and monitor production models. All data types are supported. You can do more with less. We combine machine learning with humans to filter data and select images that are relevant to your use cases. Based on your initial guidelines, you will receive sample results. We will work with you to identify and recommend best annotation practices.

Our company is the premier provider of data labeling services in AI. We cover industries like Automotive, Robotics, Fintech, Healthcare, E-commerce, Manufacturing, and Insurance. With over 500+ annotation gurus and multilingual support, we provide efficient and accurate services for both enterprise and R&D projects. Our range of services includes Computer Vision and NLP annotation, data processing, and more. Choose Label Your Data for unparalleled quality of your training datasets. Our top priority is to ensure the security and quality of client's data. To ensure the confidentiality of client data, our facilities and teams have been certified by ISO 27001 and PCI DSS (level 1). We adhere to the most important industry security standards, such as GDPR and CCPA.

Data labeling project management is made easier with the fastest data annotation tool. High level of collaboration and automation.

Keylabs is a state of the art platform that speeds up the preparation of visual data for machine-learning. Keylabs was created to provide a platform that combines state-of-the art, performance-oriented and user-friendly annotation tools with built-in machine learning and operation management capabilities. All supported dataset formats for image annotation and video annotation including semantic segmentation, cuboid 3D Point Cloud, polygons, key points, Lane annotation, bitmask. Precision up to 99.9%*

Klatch Technologies is a global provider of data services that helps companies and institutions collect and annotate data. We support Artificial Intelligence companies, research institutes, Machine Learning and Computer Vision projects in data labeling. Our specialists provide high-quality data security, rapid scalability and accuracy, as well as multilingual capability and quick turnaround time. Data Annotation Services Image Annotation Video Annotation Search Relevance Annotation for Text NLP Text classification Sentiment Analysis Image Segmentation LIDAR Annotation - Data collection services: Healthcare Training Data Chatbot Training Data All other data collection requirements IT Managed Services Moderation of Content Ecommerce Data Categorization

UHRS can help you with data validation, data validation, classification and sentiment analysis. We offer human intelligence to train machine-learning models to solve some of your most difficult problems. Judges can access UHRS from anywhere and at any time. All judges need is an internet connection and they are ready to go. You can complete tasks such as video annotation in a matter of minutes. UHRS makes it easy to classify thousands images quickly and efficiently. You can train your products and tools with improved boundary recognition, image detection, and other features using high-quality annotated data images. Classify images, semantic segmentation, object detection. Validating audio to speech, conversation, relevance. Identify the sentiment of a tweet and classify documents. Ad hoc data collection tasks, information correction/moderation, and survey.

CVAT, the leading data engine for machine-learning, allows you to annotate better. Teams at all scales use and trust CVAT for data of all sizes. CVAT's intuitive, lightning-fast user interface was developed in collaboration with real-world teams that are solving real-world issues. CVAT is used by the most ambitious AI teams in the world every day, from medical to retail to autonomous cars. CVAT can handle any input data and expected results. It works well with images, videos and even 3D. Bounding boxes and polygons. Points, skeletons. Cuboids. Trajectories. Automated interactive algorithms such as intelligent scissors, histogram equality, and others will help you annotate more efficiently. Get actionable insights from metrics such as the annotator's working hours, the number of objects per hour and more.

Manage the entire AI pipeline from raw data through to production. Build custom models that are sensitive and responsive to your operations. This will give you a competitive advantage. Create a diverse AI team that can easily deploy AI without writing a single line code. AI can be used anywhere, from the factory floor to outer space. Invest in a platform that has been proven in the most sensitive environments. You can use assisted user flows to guide you through the creation of your first model. Instead of siloing enterprise information across cloud providers and devices, centralize media into a single curated library that's optimized for discovery.

clickworker is globally the largest open crowd sourcing provider. The company has a huge number of services using a "one to many" approach where your company can use many Clickworkers to achieve the outcome you desire. Most frequently, clickworker provides customized data collection, categorization, evaluation, tagging and annotation services to create AI/ML training data for Data Scientists, and also provides SEO texts, product tags, categories and surveys for online businesses and retailers. clickworker serves most industries and applications using the skills of their 4.0M+ Clickworkers. This crowd gathers data through a wide range of micro-tasks, utilizing a sophisticated crowd-sourcing platform and fully featured mobile app.

Your AI deserves only the best data. Our unique mobile data platform, Truetag quality control and industry-leading 99% accuracy will take the stress out getting your machine learning datasets onto Tictag. Tictag’s mobile data platform is the first of its kind. It combines a user friendly interface with gamified features to produce high-quality datasets. This is technology enhanced labeling at its finest. Tictag collects and labels complex and intricate datasets with near-100% precision for AI and ML in short turnaround times. Data labeling is now faster and easier than ever. Do it right the first time. Truetag's technology-assisted quality control by Tictag ensures that your data is exactly what you need. Tictag helps people who are looking for a new source of income or a way to improve their skills by supplying them with the data they need.

Image classification, bounding boxes, polygons, curves, 3D localization Video trace. Text classification, text entity labeling. You can create your own label tool with the support of a custom task plugin. Export PascalVoc XML (The same format as CoreNLP and ImageNet). Supports Windows/Mac/CentOS/Ubuntu.

We would like to introduce ourself to your esteemed company, ROORA, which specializes in AI training data annotation services for India. We ROORA, a professional outsourcing company, offers a wide range services in outsourcing. We provide high-quality image annotation services to Machine Learning and AI-based other applications that work with Image data sets. Our services: 1. Object detection and localization 2. Full Semantic Segmentation 3. Metadata Attribution and Classification 4. Annotation for Road and Lane Marking 5. Annotation Point and Dot 6. Video Annotation 7. Annotation for Medical Use 8. 3D Lidar Labelling 9. Bounding Box Annotation

SageMaker Edge Agent allows for you to capture metadata and data based on triggers you set. This allows you to retrain existing models with real-world data, or create new models. This data can also be used for your own analysis such as model drift analysis. There are three options available for deployment. GGv2 (size 100MB) is an integrated AWS IoT deployment method. SageMaker Edge has a smaller, built-in deployment option for customers with limited device capacities. Customers who prefer a third-party deployment mechanism can plug into our user flow. Amazon SageMaker Edge Manager offers a dashboard that allows you to see the performance of all models across your fleet. The dashboard allows you to visually assess your fleet health and identify problematic models using a dashboard within the console.

Amazon SageMaker offers all the tools and libraries needed to build ML models. It allows you to iteratively test different algorithms and evaluate their accuracy to determine the best one for you. Amazon SageMaker allows you to choose from over 15 algorithms that have been optimized for SageMaker. You can also access over 150 pre-built models available from popular model zoos with just a few clicks. SageMaker offers a variety model-building tools, including RStudio and Amazon SageMaker Studio Notebooks. These allow you to run ML models on a small scale and view reports on their performance. This allows you to create high-quality working prototypes. Amazon SageMaker Studio Notebooks make it easier to build ML models and collaborate with your team. Amazon SageMaker Studio notebooks allow you to start working in seconds with Jupyter notebooks. Amazon SageMaker allows for one-click sharing of notebooks.

Your AI Data Platform High Quality Training Data for Enterprise Data Labeling Software for Machine Learning Your Kubernetes Cluster up to 3 users is free TRUSTED BY 5,000 HAPPY UBERS WORLDWIDE Images, Video, and Text Spatial Tools Quadratic Curves and Cuboids, Segmentation Box, Polygons and Lines, Keypoints, Classification tags, and More You can use the exact spatial tool that you need. All tools are easy-to-use, editable, and offer powerful ways to present your data. All tools are available as Video. Attribute Tools More Meaning. More freedom through: Radio buttons Multiple selection. Date pickers. Sliders. Conditional logic. Directional vectors. Plus, many more! Complex knowledge can be captured and encoded into your AI. Streaming Data Automation Manual labeling can be up to 10x faster than automated labeling

Anolytics offers data annotation services for image, video and text for machine learning and AI based computer vision. Anolytics provides low-cost annotation services for machine learning and the development of artificial intelligence models. It provides the annotated data in text, images, and videos using various annotation techniques. It also ensures the quality and accuracy. It is highly skilled in Image Annotation, Video Annotation, and Text Annotation. Anolytics provides all the leading data annotation services used for data training in machine learning or deep learning. It provides Bounding boxes, Semantic Segmentation and 3D Point Cloud Annotation as well as 3D Cuboid Annotation. These services are useful in fields such as healthcare, autonomous driving, drone falying, security surveillance, agriculture, and retail. Anolytics offers a scalable solution that is available quickly and at a cost-effective price for clients around the world.

Toloka AI was founded in 2014 after years spent research and experimentation. It is an open platform for collecting data and annotating it. There are over 20 000+ active monthly performers in over 100+ countries. They speak 40+ languages and generate approximately 80 million data annotations each week. Toloka is used by R&D, banking and autonomous vehicles as well as other organizations to generate machine-learning data at scale. It also harnesses the wisdom of the crowd from all over the globe. Gartner ranked Toloka as one of the most notable data labeling solutions in the market in its Hype Cycle for Data Science & ML report.

Support for various types of annotations, both on images and videos. Open-source, scalable web annotation tool. Support for simple "click and dragging" actions, and options to add more attributes. Features include the ability to copy boundaries and fit boundaries using Bezier curves. Mark the area where the driver is driving. Annotate lane markings for vision-based vehicle location and trajectory planning. Four-click method that is intuitive and accurate to encapsulate the objects of interest. Predict annotations using object tracking algorithm and interpolation algorithm to bounding boxes. Annotation prediction for object instances. Tracking features for 2D objects are now available in 3D.

Lodestar is a complete solution for creating computer vision models from video data. The world's first active learning data annotation platform allows you to label hours of video and speed up the creation of high-quality datasets and computer vision models. Automated data preparation makes it easy to drag and drop 10 hours worth of video into one project. Multiple video formats are supported and no data curation is required. Annotators and data scientists can collaborate to create a functional object detection model within an hour by using continuous model training and a shared managed dataset. Every plan comes with unlimited labels.

Innotescus is an image and video annotation platform that enables collaboration and data handling. It streamlines Computer Vision development through intuitive collaboration features, smart annotation tools and seamless data handling. Its data visualization tools and cross functional collaboration features help to identify data bias early and improve data accuracy. This allows for faster and more cost-efficient deployments of high-performance Artificial Intelligence.

SuperAnnotate is the best platform to build high-quality training datasets for NLP and computer vision. We enable machine learning teams to create highly accurate datasets and successful pipelines of ML faster with advanced tooling, QA, ML, and automation features, data curation and robust SDK, offline accessibility, and integrated annotation services. We have created a unified annotation environment by bringing together professional annotators and our annotation tool. This allows us to provide integrated software and services that will lead to better quality data and more efficient data processing.

Expand the platform to include annotation for segmentation. The Zastra repository will include algorithms that support segmentation to enable active learning of datasets. End-to-end ML opsversion control for datasets / experimental and templated pipelines to enable deployment of the model to standard cloud-based environments as well as the Edge. Bayesian deep learning advances are integrated into the active learning framework. Bayesian CNN is a specialized architecture that improves the quality of annotations. This breakthrough solution was created by our experts who have spent many hours working with you. We are still adding new features to the platform but we couldn't wait for you to take it for a spin! Active-Learning based object detection, classification, segmentation, localization, as well as object detection are some of Zastra's key capabilities. This is possible for images, text, audio, and point cloud data.

Machine teaching that is highly efficient An annotation tool powered with active learning. Prodigy is a scriptable tool that allows data scientists to do annotations themselves. This allows for a new level in rapid iteration. Transfer learning technologies allow you to train production-quality models using very few examples. Prodigy allows you to take full advantage modern machine learning by using a more agile approach for data collection. You'll be more productive, more independent, and deliver more successful projects. Prodigy combines state-of-the art insights from machine learning with user experience. You are only required to annotate examples that the model doesn't already know. The web application is flexible, powerful, and follows modern UX principles. It's simple to understand: it's designed for you to focus on one decision at the time and keep you clicking, much like Tinder for data.

Supercharge your AI with human expertise. SUPA is here to help you streamline your data at any stage: collection, curation, annotation, model validation and human feedback. Better data, better AI. SUPA is trusted by AI teams to solve their human data needs.

Amazon SageMaker Model training reduces the time and costs of training and tuning machine learning (ML), models at scale, without the need for infrastructure management. SageMaker automatically scales infrastructure up or down from one to thousands of GPUs. This allows you to take advantage of the most performant ML compute infrastructure available. You can control your training costs better because you only pay for what you use. SageMaker distributed libraries can automatically split large models across AWS GPU instances. You can also use third-party libraries like DeepSpeed, Horovod or Megatron to speed up deep learning models. You can efficiently manage your system resources using a variety of GPUs and CPUs, including P4d.24xl instances. These are the fastest training instances available in the cloud. Simply specify the location of the data and indicate the type of SageMaker instances to get started.

Amazon SageMaker Clarify is a machine learning (ML), development tool that provides purpose-built tools to help them gain more insight into their ML training data. SageMaker Clarify measures and detects potential bias using a variety metrics so that ML developers can address bias and explain model predictions. SageMaker Clarify detects potential bias in data preparation, model training, and in your model. You can, for example, check for bias due to age in your data or in your model. A detailed report will quantify the different types of possible bias. SageMaker Clarify also offers feature importance scores that allow you to explain how SageMaker Clarify makes predictions and generates explainability reports in bulk. These reports can be used to support internal or customer presentations and to identify potential problems with your model.

Amazon SageMaker Autopilot takes out the tedious work of building ML models. SageMaker Autopilot simply needs a tabular data set and the target column to predict. It will then automatically search for the best model by using different solutions. The model can then be directly deployed to production in one click. You can also iterate on the suggested solutions to further improve its quality. Even if you don't have the correct data, Amazon SageMaker Autopilot can still be used. SageMaker Autopilot fills in missing data, provides statistical insights on columns in your dataset, extracts information from non-numeric column, such as date/time information from timestamps, and automatically fills in any gaps.

Optimize ML models with real-time training metrics capture and alerting when anomalies are detected. To reduce the time and costs of training ML models, stop training when the desired accuracy has been achieved. To continuously improve resource utilization, automatically profile and monitor the system's resource utilization. Amazon SageMaker Debugger reduces troubleshooting time from days to minutes. It automatically detects and alerts you when there are common errors in training, such as too large or too small gradient values. You can view alerts in Amazon SageMaker Studio, or configure them through Amazon CloudWatch. The SageMaker Debugger SDK allows you to automatically detect new types of model-specific errors like data sampling, hyperparameter value, and out-of bound values.

Keymakr’s advanced video annotation tools, along with our professional in-house team of annotation experts, ensure the best possible results for your computer vision data needs. Annotating video while tracking objects across multiple frames. Each object in the video can be tracked and recognized even if it is captured by different cameras or video segments. We use a variety of media to create precise and human-annotated datasets. Our expertise in video annotation and labeling allows us to create custom machine-learning data sets that meet your project's needs. Improve the accuracy of existing models. We check and correct all algorithmic outputs including bounding boxes, polygon annotating, instance segmentation and semantic segmentation. Computer vision development is a complex process that requires quality training data.

Annotation solutions that are end to end, scalable and offer high accuracy & speed of turnaround. 2D/3D bounding box, polygons and polylines, landmarks & semantic segmentation to serve use cases from LiDAR to Geo-spatial imagery. Zuru's teams are working on complex computer vision algorithms that have edge cases and taxonomies. Text annotations are available in all major languages, including Bahasa, Cantonese and Hungarian. Experts in linguistic labelling who have annotated over 10 million data points across industries from Retail to BFSI and Healthcare. Zuru's team has done it all, whether it was sophisticated labelling for automation in customer centres, basic transcription or Audio diarization. Multilingual translators & interpreters workforce with a wide range of accents & dialects to help AI teams understand cultural nuances across languages and geographies.

Amazon SageMaker JumpStart can help you speed up your machine learning (ML). SageMaker JumpStart gives you access to pre-trained foundation models, pre-trained algorithms, and built-in algorithms to help you with tasks like article summarization or image generation. You can also access prebuilt solutions to common problems. You can also share ML artifacts within your organization, including notebooks and ML models, to speed up ML model building. SageMaker JumpStart offers hundreds of pre-trained models from model hubs such as TensorFlow Hub and PyTorch Hub. SageMaker Python SDK allows you to access the built-in algorithms. The built-in algorithms can be used to perform common ML tasks such as data classifications (images, text, tabular), and sentiment analysis.