An advanced cloud-based SaaS platform, currently serving the US real estate market with a focus on geo-analytics and forecasting. It integrates state-of-the-art Generative AI and Machine Learning technologies, enhancing both functionality and accuracy. The platform operates natively with Amazon Web Services (AWS) and Kubernetes, supporting multi-tenancy and ensuring robust security. Its key features include auto-scalability and high availability, providing real estate professionals with reliable, data-driven insights and predictions.
The Automated Talent Acquisition Platform offers insightful, AI-driven capabilities to optimize our recruitment process. It swiftly navigates through job applications, allowing our HR team to allocate less time to administration and more time to strategic decision-making. By enhancing efficiency and accelerating the hiring process, our solution contributes to a more productive talent acquisition strategy, fostering the continued growth and success of our company
This free DevOps course provides an extensive look at Kubernetes, blending on-premises and cloud solutions with a focus on industry best practices. It is designed for both beginners and experienced developers, covering key aspects like development process optimization, application deployment, and infrastructure scaling. The course offers deep insights into Kubernetes, preparing learners for a successful tech industry career. Organized into well-structured lessons, it includes a wealth of resources and code snippets from various external repositories. This course is an invaluable opportunity for those seeking to enhance their DevOps skills and industry knowledge.
Ellipsoidal Toolbox for MATLAB is a standalone set of easy-to-use configurable MATLAB routines and classes to perform operations with ellipsoids and hyperplanes of arbitrary dimensions.
Core library for boosting a development in Matlab. The library was originally developed as an auxilary library for [Ellipsodal Toolbox for Matlab](/project/ellipsoidal_toolbox/) project back in 2014.
PgMex is a high-performance PostgreSQL client library for Matlab that enables a Matlab-based application to communicate with PostgreSQL database in the Matlab native way by passing data in a form of matrices, multi-dimensional arrays and structures. The library is written in pure C which gives a significant performance boost for both small and data-heavy database requests. Both Windows and Linux platforms are supported.