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Welcome to the official LinkedIn page for Albumentations, the leading image augmentation library designed for computer vision tasks. With a focus on performance, ease of use, and versatility, Albumentations provides an extensive toolkit for enhancing your machine-learning models by diversifying training data through high-quality image transformations. Developed by a team of passionate AI enthusiasts and researchers, Albumentations is built with Python and offers seamless integration with popular machine learning frameworks like TensorFlow and PyTorch. Whether you're working on image classification, segmentation, object detection, or any other computer vision challenge, Albumentations accelerates your projects by making image augmentation simpler, faster, and more effective. Why Albumentations? - Performance: Optimized for speed, Albumentations ensures your data augmentation doesn't become a bottleneck in the training process. - Comprehensive: From basic transformations like flips and rotations to advanced effects like color adjustments and complex composition, Albumentations covers all your augmentation needs. - Flexible and Easy to Use: A simple yet powerful API allows for easy integration into your existing workflows, making sophisticated augmentation strategies accessible to everyone. - Community-Driven: At the heart of Albumentations is a vibrant community of developers and researchers. Contributions, feedback, and discussions are always welcome, driving the library towards constant improvement and innovation. - Whether you're a seasoned data scientist, a machine learning enthusiast, or someone just starting in computer vision, Albumentations is your go-to library for transforming images into a powerful asset for model training. Join our community, contribute, and let's push the boundaries of what's possible in computer vision together.
Datacoral provides a secure, end-to-end data infrastructure as a service, enabling data scientists and data engineers to focus on working in the data rather than the scaffolding around it. We are founded and built by the people that built data infrastructure at 21st century unicorns: Yahoo!, Facebook, Groupon, MuleSoft and Splunk. The company was incubated at Social Capital, received Series A investment from Madrona Venture Partners as well. Many of our customers aspire to become unicorns themselves. An AWS-native solution, Datacoral deploys Serverless Microservices in your VPC, the system is very secure and we never see your data values. We manage the infrastructure, you work in the data using your SQL skills. We connect to over seventy data sources and targets and follow modern Extract, Load and Transform (ELT) best practices for orchestrating data pipelines into and out of your data warehouse. Datacoral supports Amazon Redshift, Amazon Athena and Snowflake data warehouses, in which you use your favorite SQL query editor to build materialized views that transform your data. Unlike other solutions, we do not stop at simply ingesting data into a warehouse, we help orchestrate its continuous flow--from original cloud sources through landing in S3; loading into the warehouse; executing materialized views for analytics and cleansing; and publishing to data science platforms, analytics environments and even to operational systems like Salesforce. We help save our customers two to three man-years in resources, annually. We are their data engineering team, they work in their data. As a data-driven organization, you need to derive value as quickly as you can, yet data programming in the cloud can involve hundreds of technologies, many that you may need to learn. We already know them.
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