Machine Learning with Watson and Azure

If you think you don't have advanced skills in machine learning and data science, then use cloud capabilities to build applications with various ML functionalities.

Yes, machine learning with cloud computing, i.e. Intelligent cloud has lots of lot benefits like pay as you go, easily scaling up or down accordingly the demand, doesn't require any high end skills and many more.

Machine learning require lots of processing power and to get cost effective and scalable app requires dedicated servers for it.

Intelligent cloud not only give the solution of the mentioned problems, but also other benefits like chatbot services, cognitive services, big analytics tools and so on.

In this course, you'll learn and manage various cognitive services like image recognition, video analysis, speech to text, text to speech, translation, language analysis and many more.

You are about to learn Machine Learning tools and techniques on IBM Bluemix (Watson) and Microsoft Azure.

Walk through the course:

IBM Watson:

• Watson Assistant  -> Build and deploy chatbots and virtual assistants. 

• Watson Discovery  -> Uncover connections in data by combining automated ingestion with advanced AI functions. 

• Watson Speech to Text  (STT) ->Easily convert audio and voice into written text. 

• Watson Text to Speech (TTS)  ->Convert written text into natural-sounding audio in a variety of languages and voices. 

• Watson Language Translator  ->Dynamically translate news, patents or conversational documents. 

• Watson Natural Language Classifier  ->Interpret and classify natural language with confidence. 

• Watson Natural Language Understanding -> Analyze text to extract metadata from content such as concepts, entities and sentiment. 

• Watson Visual Recognition  ->Tag, classify and search visual content using machine learning. 

• Watson Tone Analyzer  ->Analyze emotions and tones in written content. 

• Watson Personality Insights -> Predict personality characteristics, needs and values through written text. 

Microsoft Azure:

• Computer Vision -> Tag, classify and search visual content using machine learning.

• Content Moderator -> Detection of potential offensive and unwanted images/videos

• Custom Vision -> Applying computer vision to your specific scenario

• Text Analysis -> Analyze text to extract metadata from content such as concepts, entities and sentiment. 

• Translator -> Dynamically translate news, patents or conversational documents. 

Now you understand coupling machine learning and cloud computing together is the most worthwhile things for the business/startups. In this learning path, you'll be doing so much. I'm sure you'll love this amazing journey and learn a lot.

Then why you're waiting for? Enroll Now !!