Machine Learning and AI using Microsoft Cognitive Services

Description

Machine Learning has always been a complex subject. No doubt the salaries of the Machine Learning experts are among the highest. It is equally true that it has a steep learning curve. In this course, we are going to make it super easy for any developer to embed Machine Learning and AI in their applications. You will not need all the complexities of Mathematics and Statistics.

Welcome to the course on Machine Learning using Azure Cognitive Services which is part of the Artificial Intelligence services of Microsoft.

This course covers Azure Cognitive APIs for Visual Features including Face Detection, Tagging the content of an image, OCR as well as Text Analytics for Language Detection, Sentiment Analysis and Key Phrase extraction. The course is very hands on and covers the implementation of these APIs using Python as well as Javascript.

Let me ask you,

1. Do you want to develop Machine Learning based apps that will have vision intelligence such as identifying faces, tag objects etc?

2. Do you want to develop apps that will have high caliber machine learning for Text Analytics?

3. Do want to do sentiment analysis of the texts using Machine Learning?

4. Do you want to identify and tag various objects within an image?

You may want to develop such an application that processes, texts written or spoken words of a user using Natural Language Processing. You may also want to develop some cool funny apps, but don't know how to identify the different aspects of a face such as exactly where the eyes or nose are.

With cognitive services you will be able to build all such or even more types of applications.

If you try to build those using traditional means of Machine Learning, you may face severe challenges.

• First of all, there are just too many frameworks related to Machine Learning

• Then there are so many languages. It may take you months to learn and master Machine Learning using these technologies.... and every framework has its own strengths and weaknesses.

• The next challenge for a production grade Machine Learning application which can give quick response time will be the type of infrastructure that's required. You may end up owning or leasing very high end computing devices such as specialized virtual machines, GPUs and so on..

• The last challenge but one of the most critical ones is the expertise.

With the emergence of the cloud, there is however, another model that has evolved which is Machine Learning As a Service. With years of research by top Data Scientists around the world, Microsoft has developed Cognitive Services. The Azure Cognitive Services, allows you to simply use the APIs and get started with embedding Machine Learning capabilities in your applications.

So hit the enrol button and we are so excited to see you inside the course....

Who this course is for:

• Any software engineer wants make their application intelligent without knowledge of Machine Learning and Deep Learning
• Anyone wants to use top deep learning model by worlds best ML and DL experts
• Any organization who want to use ready made high level cognitive task API without Hiring Data Scientist
• Anyone who don't know Machine learning and Deep learning like advanced technology, still wants use Vision, Speech, Face and Text analytics API in minimum time.
• Anyone wants to learn Microsoft azure cognitive Services with Minimum learning curve.

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