One Unified Time Tracking Software For Projects, Billing, Pay and Compliance
For companies of all sizes looking for a Time Tracking software
Replicon's time-tracking platform is scalable and configurable to support the diverse needs of small, mid & large businesses with a remote and globally distributed workforce. Replicon’s Time Tracking is a cloud-based, enterprise-grade solution that tracks employee time across projects, tasks, presence, and absence to facilitate client billing, project costing, and compliant payroll processing. The scalable and configurable platform offers seamless integration with common business technology stacks, such as ERP, CRM, Accounting, and payroll solutions. With AI-powered time capture, mobile apps, and labor compliance as a service, Replicon makes time tracking hassle-free.
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BrandMail Email Signatures for Outlook
Leverage every email as an opportunity to brand consistently and minimise the security risks associated with the tampering of HTML signatures.
BrandMail®, developed by BrandQuantum, is a software solution that seamlessly integrates with Microsoft Outlook to empower every employee in the organisation to automatically create consistently branded emails via a single toolbar that provides access to brand standards and the latest pre-approved content.
Reinforced Recommendation toolkit built around pytorch 1.7
This is my school project. It focuses on Reinforcement Learning for personalized news recommendation. The main distinction is that it tries to solve online off-policy learning with dynamically generated item embeddings. I want to create a library with SOTA algorithms for reinforcement learning recommendation, providing the level of abstraction you like.
Implement AlphaZero/AlphaGo Zero methods on Chinese chess
ChineseChess-AlphaZero is a project that implements the AlphaZero algorithm for the game of Chinese Chess (Xiangqi). It adapts DeepMind’s AlphaZero method—combining neural networks and Monte Carlo Tree Search (MCTS)—to learn and play Chinese Chess without prior human data. The system includes self-play, training, and evaluation pipelines tailored to Xiangqi's unique game mechanics.
This project provides a framework for testing and comparing different machine learning algorithms (particularly reinforcement learning methods) in different scenarios. Its intended area of application is in research and education.