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Optimizing Risk Management With AI

AI, Data Science3 min read

Mandar Avhad

Meet Mandar Avhad

Data Science & AI Student @ Mumbai University

Mumbai, India 

Mandar Avhad is a Data Science Python developer who experiments in projects based on machine and deep learning integrating computer vision.

He is a graduate student from the University of Mumbai and did an internship in a firm called Care Risk Solutions addressing the area of enterprise risk management for banking implementing artificial intelligence.

What inspired you to pursue a career in Artificial Intelligence?

I always had a strong background in Science and Engineering. Since childhood, I was fascinated by technology and I witnessed how it was in the past and how it is now, growing bigger and better.

I always dreamt of being a part of the technology that can make things better and easy for the world.

I started digging into the technology and got to discover many news things which most of the common people are unaware of. In today’s world, we all get to experience this technology but we do not know when and where.

Like when you search something on google, and later it refers you to things similar to your searches, many of them don’t know what technology Google uses. But when I got to how vast and how useful this technology can be, I developed more interest in learning and experimenting with this technology. This was the reason I transitioned towards this field.

I strongly feel that Artificial Intelligence can help us achieve things that were difficult for humans to achieve alone. We can witness how technology is helping us do things in a better and efficient way.

What limitations linear regression have for predicting product sales or housing prices?

The main limitation of Linear Regression is the assumption of linearity between the dependent and independent variables. But in the real world, the data does not always have a straight-line relationship between dependent and independent variables.

Also, it is prone to overfitting and noise. It is also sensitive to outliers.

Linear Regression is a great tool to analyze the relationships among the variables but it isn’t recommended for most practical applications because it over-simplifies real-world problems by assuming a linear relationship among the variables

Mention where Ai could have a big impact? and Why?

Every industry is implementing and experimenting with AI in such a way to help them be more productive, profitable, and innovative.

AI has a great impact on the Health care industry. It’s playing a vital role in diagnosing, analyzing, and predicting various types of diseases. Also, it’s helping in achieving the results much faster than the traditional method.

Agriculture which is an important sector is trying to implement AI. AI is helping in monitoring and adjusting the parameters which were not possible for traditional methods.

This is helping us grow any crops independent of natural parameters that are unstable. AI is boosting production and productivity. Talking about Security and Surveillance, we all know how crucial it is.

AI has brought forward real-time monitoring of data with intelligent analysis. It has a great impact on securities of airports, stadiums, malls, etc where the chances of threats are more and have to be avoided. AI can quickly alert us if there’s something suspicious that our human eye could miss.

In almost every industry, AI can have a greater impact if implemented wisely, to achieve more efficiency and help humans.

What role models or books have been your greatest inspiration to get into AI?

For me, the role model companies are Apple, Google, and Amazon.

All these companies have used AI in such a way that has helped the company grow bigger and better. Apple using the technology in its smartwatches and smartphones, Siri being one of its outcomes, etc.

Amazon using the technology in e-commerce, web services, and of-course the smart Alexa.

Google using technology to make things easier and friendlier for its users. Also, I see a lot of startups who have a great vision and are working towards it.

Some of them are actually taking a problem and bringing solutions to the world.

Apart from these, I admire the work of Andrew NG and no doubt why he’s considered as one of the greatest contributors to the AI community.

From founding Google brain to being Professor at Stanford and working on research to founding the Coursera platform, his work in this field has been huge and inspiring.

It's great to follow people, follow their work and vision. But, one should not try to become the next Steve Jobs, next to Mark Zuckerberg, but be their own version.

More importantly, one should always try to be original, follow their own aspirations.