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Quantathon 2.0

The AI ML Track is focused on exploring the vast potential of artificial intelligence and machine learning in solving complex challenges across various domains.Participants in this track will have the opportunity to work on cutting- edge projects, applying state - of - the - art algorithms and techniques to real - world datasets.
From predictive analytics and natural language processing to computer vision and reinforcement learning, the AI ML Track encompasses a wide range of exciting areas in the field of AI.Participants can choose projects aligned with their interests, enabling them to delve deep into specific subdomains of AI and build their expertise

AI/ML

The Core Quantum Track delves into the fundamental concepts of quantum computing and quantum technologies. Participants will embark on a quest to understand the principles behind quantum mechanics, quantum algorithms, and quantum hardware. The track aims to provide a hands-on experience in working with quantum programming languages, simulators, and actual quantum devices.
From exploring quantum superposition and entanglement to implementing quantum algorithms such as Shor's algorithm and Grover's algorithm, this track will challenge participants to stretch their minds and develop quantum solutions to real-world problems. Participants will gain insights into the unique advantages and limitations of quantum computing compared to classical computing.

Core Quantum

The Open Innovation Track is a blank canvas where participants are encouraged to think outside the box and tackle problems from various domains. There are no predefined themes or restrictions in this track, allowing participants to explore a wide array of topics that spark their curiosity and passion.Whether it's developing cutting-edge technologies, addressing societal issues, or creating novel applications, the track invites participants to let their imaginations run wild and embrace the freedom to innovate.
Participants can choose to work on solo projects, form cross-functional teams, or collaborate with other participants during the Hackathon. They are encouraged to bring diverse skill sets, backgrounds, and perspectives to the table, fostering an environment of open dialogue and co-creation.

Open Innovation

Quantum machine learning is a research area that explores the interplay of ideas from quantum computing and machine learning. Quantum machine learning (QML) is an interdisciplinary field that integrates quantum physics concepts with machine learning to produce algorithms that employ quantum computer’s processing power to address specific sorts of issues more effectively than classical computers. The quantum computer, a whole new class of computing system, increases the hardware available for machine learning through quantum machine learning. Quantum theory, which is based on completely different physics, is the foundation for information processing using quantum computers.

Quantum Machine Learning

Read about the bounty details and find code templates for Polygon here: [https://nsb.dev/polygon-bounty](https://nsb.dev/polygon-bounty).