The basis of Quantum Computing relies on the concept of a qubit which denotes a super-positioned state of a normal bit. In layman terms, the bit can attain a state where it represents both 1 and 0 at the same time and that leads to the exponentially higher computational capabilities. Machine learning on massive data is quite hard as it leads to several problems such as over-fitting,
extra generalization and much more. With the computational power of a quantum computer, there will be no bounds untouched.
Machine Learning has a wide variety of approaches to solving problems. Some, if not most of these problems require large amounts of data. While there are techniques to solve such problems there is a limit. With the help of quantum computation not only can these be solved but there will be a
larger generation of parameters which will lead to better foundations and results. Problems pertaining to tensor factorization and inference in graphical models can be dealt with as well. …
Writing blogs has become a new way to portray one’s technical prowess. The process is quite easy with platforms such as medium and it is a great way to produce helpful material for others to discover. This blog will cover 5 tools which will help you create better articles and save time in doing so.
Just like everyone else, the lockdown had pushed me to explore something new during the month of April 2020. I was looking for some new avenues to look into to improve my personal portfolio and so I applied to blog with TRN (The Research Nest). My main topic of focus was on Artificial Intelligence and I delivered 10 articles during the tenure. Here are my major takeaways from the experience —
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Sub-Domains are also available in each of the above domains for the students to work in their specific areas of interest. …