LNMHacks 3.0

Hacks in any theme also belong to General.

Innovation in financial services have just begun to come through, but this field is different than others. The challenge is not only in providing newer and more innovative services that either benefits a customer or helps investors and banker make better decisions. The challenge is also in securing these systems from the ever growing numbers of vulnerabilities and from the malicious intent of wrong doers. If you can build new and innovative financial solutions, while building a cyber fort knox, then Fintech needs you.

The power couple of technology and educational content has revolutionised how people learn today. From online universities like Coursera and Udacity, to learning management solutions like Moodle - technology has changed the art of education for the better. But we’re still scratching the surface. With the advent of big data technology, mobility and the maturing of machine learning and artificial intelligence, the world is now ready for ed-tech 2.0. Think you can harness these powerful tools and give a new dimension to educational technology?

A world of devices connected by internet opens up opportunities for us that were previously unthinkable. The fact that devices can now be connected to each other, share data and take intelligent decisions by talking to other devices can disrupt the way we interact with our surroundings. Build applications on Internet of Things that help us improve our experience in our day to day life.

A blockchain, originally block chain, is a growing list of records, called blocks, which are linked using cryptography. Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. By design, a blockchain is resistant to modification of the data.

Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed. The name machine learning was coined in 1959 by Arthur Samuel.

Computer vision is an interdisciplinary field that deals with how computers can be made to gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do.