Machine learning (ML) is touted as the most critical skill of current times. Artificial intelligence (AI), an application of ML, is becoming pervasive. From autonomous vehicles to self-tuned databases, AI and ML are found everywhere.  Almost every domain and industry vertical are getting impacted by AI and ML. Platform companies with massive investments in AI research are shipping new tools and frameworks at a rapid pace.

Despite the interest and a sense of urgency, developers are struggling to learn the essential skills required to master ML.

Here are some of the challenges that developers need to overcome before mastering machine learning.

Check this out: Forbes: ML and Python

Robot-software læser fakturaer og klarer betalingen af lægeerklæringer i Odense kommune:

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Humans have officially given their voice to machines.

A research paper published by Google this month—which has not been peer reviewed—details a text-to-speech system called Tacotron 2, which claims near-human accuracy at imitating audio of a person speaking from text.

Check it out here: Google’s voice-generating AI is now indistinguishable from humans

 

 

The 2017 RPA Landscape – Check this out: RPA 2017 Landscape