PGPDM in Data Science and Machine Learning

Leading studies predict that the Deep Learning market is likely to exceed $20 billion by 2024, growing at a compounded annual growth rate of 4 per cent. Deep learning algorithms are more likely to become more sophisticated with passing time thereby possessing the ability to take huge amount of data generated from audio, video and images and process them to make business-friendly predictions. Deep Learning will be strongly associated with modern online services where organizations will use their predictive capabilities to provide more customised offerings to their audiences around the world. In the following paragraphs we look at top 5 Deep Learning trends that are most likely to dominate the coming year. Training dataset bias and its impact on AI It is natural for human bias to creep into a majority of decision making models. The difference and variability of algorithms dealing with AI is significantly impacted by the inputs that they are fed. Data scientists are of the opin...

A deep learning system draws textual clues from the context of images to define them without the requirement for prior human interpretations. Since its beginnings, deep learning, as both a scientific discipline and an industry, has come a long way. From cellphone assistants to pattern recognition software system, security solutions, and other applications, deep learning has become a multi-billion dollar industry poised for exponential growth over the few next years. However to attain their full potential, these softwares have to “learn” how to learn on their own. Self-Supervised Deep Learning The power and application of deep learning is all about its ability to identify different kinds of patterns like voices, faces, images, objects, and codes. AI software doesn’t understand what these things actually are, and all they perceive is digital data, and they’re quite good at that. The great computer vision competence of deep learning algorithms assists them to set these things a...

The mantra for advancement in technology is to reduce or replace human labor with machines. Traditional human driven systems are being replaced by smart machines and automation. In other words, we can say that the dependence on human decision-making is dwindling very rapidly. If we consider an example of autonomous vehicles like self-driven cars, we can see how AI and machine learning applications are extensively used in self-driven cars these days to avoid collisions, enhance cruise control, self-parking, detect blind-spots, provide drifting warnings and more. All this has become possible with the advancements in technology and the advent of automation in the technology segment, which has transformed the way we deal with objects in our daily life. Now, let’s take a quick look at the most promising AI and machine learning trends for 2018.  Healthcare Sector: So Much Advancement Is Going on  In the last few years, we have seen how the healthcare industry has embrace...

If you don’t have a team of data science professionals in your organization, chances are you will have one soon. According to the Edvancer study, data science and analytics is one of the fastest growing job fields in India. As every business organization is producing data on a large scale, it becomes important for enterprises from different industry verticals such as retail, healthcare, manufacturing, information technology (IT) and others to strengthen their data teams. India is developing into one of the world’s data science capitals with renowned brands, including PayPal, Mercedes-Benz, AIG and Walmart setting up data science centers in the country. Furthermore, research from the Everest Group clearly indicates that India holds the lion’s share of the global analytics services market.   The number of data science and analytics jobs in India nearly doubled from April 2016 to April 2017. Today, many large and mid-sized business enterprises are looking for skilled professional...