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Even with technology, sometimes we believe in fairy tales. A fairy tale is a story with a "fantastic and magical setting or magical influences within a story." I hadn't thought much about fairy tales recently, until I began reviewing the number of online case studies about artificial intelligence (AI) in companies. In most of these case studies, the bottom line was that an AI solution had been successfully implemented. However, when I reviewed the stories for business outcomes or results, the results weren't there.
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Supervised learning is one of the most widely used machine learning approaches. It can be useful for predicting financial results, detecting fraud, recognizing objects in images and evaluating or assessing risk. The aim of supervised learning is to allow machine learning functions to work in such a way that enables the input data to be used to predict the output class for each new data instance for which the classification is not already known. With supervised learning, the input data and output data (also called the class) are known in advance. This allows the model to be trained so that it produces the best predictions of classes for the training data by knowing when the model did and did not make a classification error (Figure 1).
Yes, the world is seeing an advancement by virtue of technology. Implementing machine learning has aided in a lot of fields and made remarkable inventions as well. Seeing the progress companies have made because of machine learning (ML) has made almost every company to try its hands on the same and have miserably failed in it. What might have gone wrong here? Experts believe that the strategies implemented by the companies failed to work the way they were pictured to be.
The ancient Silk Road, once the longest overland trade route, ran over 4,000 miles long. Today nestled in Eurasia's heart along the Silk Road is the national railway company – Kazakhsthan Temir Zholy (KTZ). Though traversing across this historic pathway sounds rather cool, the complex geography and harsh weather conditions propose serious challenges in operating cargo and passenger transportation. KTZ is a crucial part of Kazakhstan – the world's ninth-largest country – and its economy. This railway company knew the importance of having a seamless operating model in order to maintain its current operations, both on and off the track.
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Today, most companies are using Python for AI and Machine Learning. With predictive analytics and pattern recognition becoming more popular than every, Python development services are a priority for high-scale enterprises and startups. Python developers are in high-demand – mostly because of what they can achieve with the language. AI programming languages need to be powerful, scalable, and readable. Python code delivers on all three. While there are other technology stacks for AI-based projects, Python has turned out to be the best programming language for AI.
Algorithms are the heartbeat of applications, but they may not be perceived as entirely benign by their intended beneficiaries. Most educated people know that an algorithm is simply any stepwise computational procedure. Most computer programs are algorithms of one sort of another. Embedded in operational applications, algorithms make decisions, take actions, and deliver results continuously, reliably, and invisibly. But on the odd occasion that an algorithm stings -- encroaching on customer privacy, refusing them a home loan, or perhaps targeting them with a barrage of objectionable solicitation -- stakeholders' understandable reaction may be to swat back in anger, and possibly with legal action.