Machine learning is a method of data analysis that automates analytical model building. It's a branch of Artificial Intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human interaction.
This series of articles intend to elaborate the usage of Azure Machine learning and usage of different machine learning tools in Azure ML studio. This is the first post and it walks you through the introduction to the Azure ML studio and how to upload data to the tool.
Two most widely adopted machine learning methods are,
- Supervised learning: algorithms are trained using labeled examples, such as an input where the desired output is known
- Unsupervised learning: is used against data that has no historical labels. The System is not told the "right answer." The algorithm must figure out what is being shown.
Differences between data mining, machine learning and deep learning
- Data mining is about to identify previously unknown patterns from data. It might involve traditional statistical methods and machine learning.
- Deep learning combines advances in computing power and special types of neural networks to learn complicated patterns in large amounts of data. Deep learning techniques are currently state of the art for identifying objects in images and words in sounds.
Cognitive Services in Azure
Vision
Image-processing algorithms to smartly identify, caption and moderate your pictures.
Computer Vision - Analyse content in images and video.
Custom Vision - Customize image recognition to fit your business needs.
Face - Detect and identify people and emotions in images.
Form Recogniser - Extract text, key-value pairs and tables from documents.
Video Indexer - Analyze the visual and audio channels of a video, and index its content.
APIs for AI related to vision example https://azure.microsoft.com/en-gb/services/cognitive-services/#api
Computer Vision:
Extract rich information from images to categorize and process visual data—and perform machine-assisted moderation of images to help curate your services.
- Read text in images
- Recognize celebrities and landmarks
- Analyze video in near real-time
- Generate a thumbnail
Face API :
Detect human faces, compare similar ones, Organize based on attributes, Identify previously tagged people
Other Cognitive service categories and services include,
Speech : Features include speech to text, speaker recognition, text to speech
Language : Text Analytics, Text translate, Content moderator
Knowledge : QnA Maker
You can use https://www.qnamaker.ai/ to create a Q and A and integrate it with bot framework. Then you can embed it in sites
I hope this has been informative and thank you for reading!
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