Total Products under this Category: 2,450
Last updated: November 01, 2026
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Deep Learning based low-code solution which generates HTML, CSS, HTML-JET code from hand drawn wire frames as well as visual designs.
Autocode Text To Golang Code Recommender takes a code related user text query as input and returns 3 optimal code recommendations from Github that will be syntactically and semantically correct. Considering the ever increasing number of programming languages and the frameworks that are built around them, it is very difficult to be technically fluent in all of them. Another challenge is the amount of code development time and effort spent on looking up efficient solutions to solve a problem. This solution helps in addressing these practical problems faced by the developer community.
Autocode Text To PHP Code Recommender takes a code related user text query as input and returns 3 optimal PHP code recommendations from Github that will be syntactically and semantically correct. Considering the ever increasing number of programming languages and the frameworks that are built around them, it is very difficult to be technically fluent in all of them. Another challenge is the amount of code development time and effort spent on looking up efficient solutions to solve a problem. This solution helps in addressing these practical problems faced by the developer community
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Autocode Text To Ruby Code Recommender takes a code related user text query as input and returns 3 optimal Ruby code recommendations from Github that will be syntactically and semantically correct. Considering the ever increasing number of programming languages and the frameworks that are built around them, it is very difficult to be technically fluent in all of them. Another challenge is the amount of code development time and effort spent on looking up efficient solutions to solve a problem. This solution helps in addressing these practical problems faced by the developer community.
This solution automatically identifies and trains the best performing deep learning model for tabular data.
The algorithm trains a sparse autoencoder model to predict on classification datasets directly from CSV data.
The solution performs automated feature engineering steps like feature selection and can remove rare levels from features.
The Automatic License Plate Recognition (ALPR software by Clear Image AI is a robust solution designed to accurately identify and process vehicle license plates from various image sources. Leveraging advanced computer vision and machine learning technologies, this software ensures high precision in diverse conditions, including low-resolution images, challenging angles, and varying lighting scenarios. It is optimized for deployment across multiple countries, making it suitable for global applications. Key Features and Functionality: - High Accuracy: Utilizes sophisticated algorithms to deliver precise license plate recognition, even in suboptimal imaging conditions. - Versatile Input Compatibility: Capable of processing live camera feeds, video files, and still images, providing flexibility in integration. - Global Optimization: Tailored to recognize license plates from over 90 countries, accommodating various plate designs and formats. - Comprehensive Vehicle Data Extraction: Beyond license plate numbers, the software identifies vehicle attributes such as make, model, color, and direction of travel. - Adaptability to Challenging Conditions: Effectively processes images with issues like blurriness, low resolution, and difficult angles, ensuring reliable performance. Primary Value and User Solutions: This ALPR software addresses the critical need for efficient and accurate vehicle identification in sectors such as law enforcement, traffic management, and security. By automating the recognition process, it reduces manual workload, enhances operational efficiency, and supports real-time decision-making. Its adaptability to various environmental conditions and compatibility with multiple input sources make it a versatile tool for organizations aiming to implement or upgrade their vehicle recognition systems.
The AV1 Encoder Optimized for VoD (4K/8K HDR is a high-performance video encoding solution designed to deliver superior quality video-on-demand (VoD content at reduced bitrates. Leveraging the advanced AV1 codec, this encoder supports ultra-high-definition resolutions up to 8K and high dynamic range (HDR formats, ensuring an immersive viewing experience across various devices. Key Features and Functionality: - Ultra-High-Definition Support: Encodes video content in resolutions up to 8K, catering to the growing demand for high-resolution media. - High Dynamic Range (HDR: Supports multiple HDR formats, including HDR10 and Dolby Vision, enhancing color depth and contrast for a more realistic visual experience. - Advanced Compression Efficiency: Utilizes the AV1 codec to achieve higher compression efficiency compared to traditional codecs like H.264 and HEVC, enabling high-quality video delivery at lower bitrates. - Multi-Codec Support: In addition to AV1, the encoder supports other codecs such as VP9, HEVC (H.265, and H.264, providing flexibility in encoding options. - Content Security: Integrates with multiple digital rights management (DRM and watermarking providers, ensuring secure video delivery up to 8K resolution. - Deployment Flexibility: Offers cloud-based deployment options, allowing processing within a Virtual Private Cloud (VPC environment or as a fully managed cloud service. Primary Value and User Benefits: This encoder addresses the critical need for delivering high-quality VoD content while optimizing bandwidth usage and storage costs. By employing the AV1 codec, it enables content providers to stream ultra-high-definition videos with enhanced visual quality at significantly lower bitrates, making it ideal for bandwidth-constrained networks. The support for multiple HDR formats ensures that viewers receive a rich and immersive experience, while the integration with DRM systems guarantees content security. Additionally, its flexible deployment options allow for seamless integration into existing workflows, providing scalability and efficiency for media and entertainment companies aiming to meet the increasing demand for high-resolution, high-quality video content.
With Aventra IRON, you deliver targeted workload performance requirements with cost effective resources. Aventra's AMI's accelerate compute, memory and storage optimized instances; high-performance computing instances; and instances used for general purpose applications.
TurnKey Avideo helps save you time and money by providing a ready-to-run Avideo solution that is secure, supported and easy to maintain. The system auto-updates itself with security fixes and is built in a transparent 100% open source process free of hidden backdoors
AWS CodePipeline is a fully managed continuous integration and continuous delivery (CI/CD) service that automates the build, test, and deployment phases of application release processes. By orchestrating the entire workflow from code commit to production, CodePipeline enables developers to deliver software updates rapidly and reliably, ensuring consistent and error-free deployments. Key Features and Functionality: - CI/CD Pipeline Design and Setup: Facilitates the creation and configuration of automated pipelines tailored to specific development workflows. - Integration with Various Tools: Seamlessly integrates with AWS services like CodeCommit, as well as third-party tools such as GitHub and Jenkins, allowing flexibility in source control and build environments. - Automated Testing and Deployment: Supports the automation of testing and deployment processes, enabling continuous delivery and reducing manual intervention. Primary Value and Problem Solved: AWS CodePipeline addresses the challenges of manual software release processes by providing a streamlined, automated solution for CI/CD. It enhances developer productivity by eliminating the need for manual build and deployment steps, reduces the risk of errors through consistent workflows, and accelerates the delivery of new features and updates to end-users. This automation ensures that applications are released faster and with higher reliability, meeting the demands of modern software development practices.
Average Rating: 5.0/5.0
Total Reviews: 1
"Feature-Rich, Fully Managed CI/CD with Seamless AWS Integrations"
Rating: 5.0/5.0 stars
— Jahangeer .
The 'Azure Data Science Hub (DSVM)' is a 'Ubuntu 20.04.2' VM that has several popular tools for data exploration, analysis, modeling & development pre installed. The installed AI/ML environment is available in browser via JupyterHub and Jupyter notebooks with separate Jupyter environment for a single developer or individual user of a team, saving you time, cost and server administration efforts.
This product has charges associated with it for seller support, includes AWS Deep Learning AMI Ubuntu 16.04 Version 38.0 and includes support. AWS Deep Learning Base AMI provides a foundational platform for deep learning on AWS EC2 with NVIDIA CUDA, cuDNN, NCCL, GPU Drivers, Intel MKL-DNN, Docker, NVIDIA-Docker, EFA, and AWS Neuron support. This AMI is suitable for deploying your own custom deep learning environment at scale. For example, for machine learning developers contributing to open source deep learning framework enhancements, the AWS Deep Learning Base AMI provides a foundation for installing your custom configurations and forked repositories to test out new framework features. You could also be a Machine Learning / AI startup with a highly specialized deep learning setup that needs a foundation to run on a cloud-scale infrastructure.
