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Machine Learning in enterprises is complex and involves many steps. Below is a complete lifecycle of a Data Science project as described by the Team Data Science Process (TDSP), which is a popular approach to structure data science projects. 
Artificial Intelligence, Machine Learning, and IT Automation are emerging technologies today. As per research, organizations who started adopting these practices are growing rapidly.
Gartner report says, “AI will be a top 5 investment priority for more than 30 percent of CIOs.”
The use of AI in policing to date has largely been in areas such as facial recognition and helping to deploy resources in the most effective ways, but a recent study led by Northumbria University highlights how it can also help to crack unsolved crimes, especially by providing insights into the weapons used in committing the crime.
“Machine learning uses a series of algorithms to model complex data relationships,” the authors say. “Through careful fine-tuning, these can be applied to predict important characteristics of the ammunition used in a particular shooting event from those of the respective gunshot residue (GSR) deposited on surrounding surfaces or items, such as spent cases, wounds, and, potentially, also the shooter’s hands.”
SAE Institute from Australia is considered the front-runner in creative studies. They recently ran a survey to understand the general sentiment of students and identify key areas of improvement. This case study describes how ParallelDots carried out a detailed survey analysis to make sense of the student responses and derived specific insights from this data. 750 students responded to the survey, resulting in a total of 4500 comments.
Traditional methods of survey analysis suffer from multiple human biases and are intensive in terms of effort as well as time. Knowing this, the institute decided to outsource the project to ParallelDots.
Artificial Intelligence is getting deeper into our daily lives, but this is not as scary as many may think. With Artificial Intelligence, we have seen things getting better and easier for us but this change does not stop at homes. Today many businesses are coming forward to use AI in new different ways so as to engage their customers, drive sales and make business processes simpler. In short, the demand for Artificial Intelligence development services will go high in the coming years.
We have already seen how Facebook was using AI to improve its ad campaigns as well as seen the effective use of AI-powered chatbots. So, what’s next? What should we expect out of Artificial Intelligence in the new year to boost business success?
Millions of Americans make decisions based on the recommendations of Artificial Intelligence, and many don't even realize what's happening.
From Netflix's "top picks for you," and Spotify's recommended playlists and artists, to even the profiles shown on dating applications, Artificial Intelligence (AI) is using algorithms to offer users suggestions designed to match our interests. But how much do people really trust those recommendations?
Artificial intelligence (AI), Chatbots and Blockchain are some of the key technologies which will disrupt the financial services industry in the coming days. Artificial Intelligence AI is a collection of machine learning, natural language processing, and cognitive computing designed for scale. This scalability is exciting, as it can create exponential growth and deliver today’s required […]
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