Artificial Intelligence has made major strides in recent years. It has found application is different industrial verticals and businesses. It has revolutionized and revamped business processes and operations, which has resulted in increased efficiency and productivity. AI allows any particular digital device to easily observe as well as recognize a subject or object, deeply understand it and reply to different recognizable messages. Also, it can easily make decisions as well as learn to adapt its behaviour as well as the thinking process as it completely analyses the huge volume of data points.

My article in Data Driven Investor published 29th of September 2019. Data Driven Investor: In the Digital Economy You are For Sale. I can get anywhere by plane within a few hours. Flight has never been so accessible and affordable. Think how much data needs to be sent, received and processed to make my journey easy. There are online searches, airline advertisements, price comparisons, flight bookings, ticket purchases, credit card transactions, promotions, transfers, connections, and luggage checking and handling.

The field of AI (artificial intelligence), to those on the outside, must appear to be an orderly gathering of intellectuals collaborating at the cutting edge of technology. The reality is a bit different. Last year, Elon Musk made headlines by describing AI as a "fundamental risk to the existence of civilization." More recently, Google CEO Eric Schmidt suggested that the answer to fears about AI was to police it and offered the example of finding a way to police the misuse of the telephone because of its possible misuse by some individuals with bad intentions rather than not inventing the phone at all. One of the biggest misconceptions surrounding AI is that most individuals think that humanity is close to it, although in fact the reality is quite different. Although a great deal has been learned about how to engineer certain narrow problems like speech recognition in ways which could not have been imagined five or ten years ago, the idea of having machines that can reason about the world in the ways that human-beings can is still implausible.

"We must develop a comprehensive global shared view of how technology is affecting our lives and reshaping the economic and social environments." Emboldened by the challenge, Nazareen Ebrahim is ready to answer the call to take on and profit amid the Fourth Industrial Revolution. Ebrahim is a senior media, communications and technology practitioner with a background in media strategy; project management; content development; training and facilitation; and radio and television presenting and production. She leads the artificial intelligence research team at Socially Acceptable, of which she is the CEO and founder. The company produced a 12-part artificial intelligence series that aims to educate professionals and the general public on artificial intelligence.

Before we cover some Machine Learning finance applications, let's first understand what Machine Learning is. Machine Learning (ML) is a part of data science that uses different models to analyze data and make predictions. The cool thing about machine learning is that, just like how babies learn to walk and speak through experience, Machine Learning Software also learns how to analyze data from experience. You don't need to explicitly teach it anything. You simply give it a set of data for which results are already known and let it process it to identify patterns in the data and corresponding results.