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Machine Learning Technology Stack

Read dzones 2019 machine learning trend report to see the future impact machine learning will have. Machine learning and advanced analytics in general requires a very different technology stack to the mibi implementations of old.

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According to gartners hype cycle machine learning is the hot new trend in the technology industry.

Machine learning technology stack. Broadly speaking there are three core considerations to bear in mind. Heres probably the most common. The expectations from machine learning and its associated fields are for multiple reasons. Were specialized in developing custom ai and machine learning solutions. An excellent thing in the machine learning world right now is that a lot of frameworks built are open sourced and free to use. If machine learning is to deliver new insights rapidly to support a real time service then businesses need to think again. Mindtitan is an artificial intelligence development company founded to help companies understand and apply ai. Machine learning is full of potential and there are enormous possibilities to exploit it. In the last few chapters we explored some of the important and relevant aspects of machine learning. As the use of machine learning and specifically compute intensive deep learning technology is booming across research and the industry the market for building the machine learning stack has exploded. The ml part is insensitive to your choice of front end assuming webapp. For example googles tensorflow a free machine learning library has made their code open source and has revolutionized the working culture of machine learning. As many of us in the industry know machine learning and neural networks are certainly nothing new. Why all the hype and excitement around artificial intelligence big data machine learning and deep learning. For the back end you should consider using one of the ml as a service apis quick to get started.

The buzz however this time around continue reading machine learning. While r compares really well with python in basic ml deep learning is more commonly done in python even though tensorflow is available in r. For data work at most companies python and r are the obvious choices. For an app there are a multitude of stacks available to you. Take a look at this article which explains some of the elements contained in a ai stack. Machine learning is a large and evolving field. And best of all ai services on aws dont require machine learning experience.