What is Azure Machine Learning?

Jul 20, 2019 Azure, Azure ML, Machine Learning, 2458 Views

In This Article, you'll learn all about Azure ML (Machine Learning).

Before we start with the understanding of what is Azure Databricks, we should know –

I would like to explain the short information about ‘what is artificial intelligence and machine learning’ before jump into Azure machine learning.

Artificial Intelligence –

In simple words ‘Artificial Intelligence (AI)’ is the artificial creation of the system like a human who can observe, react, learn, plan and process the instructions and provide intelligence on it.
It is rapidly emerging technology and the internet enables technology.
Sometimes AI is also called as Machine Learning.

Machine Learning –

Machine learning is not new. It is a subset of Artificial Intelligence (AI).
The algorithm is a sequence of activities/actions/steps used to solve the problem.
Implement the algorithm and its models are called machine learning in the computer world.
Today, developing the new algorithm to instruct the computer to run it is the key to advanced technology.
Important
1. Machine learning is a data science technique that allows computers to use existing data to forecast future behaviors, outcomes, and trends.
2. Machine learning works on the mathematical model and builds by using the sample data.
3. Machine Learning has the capability to learn and IMPROVE from experience WITHOUT explicit programmed.
Examples
1. How to email system tracks the email is spam email.
2. How an online shopping system shows a similar product which you are looking for.
Types
1. Supervised Learning – We have trained the model by data sets.
2. Unsupervised Learning – Machine learning model learns the data and finds the patterns and relationships in the data. Based on the pattern and relationships model is trained.
3. Reinforcement Learning – Machine learning model will find out the best outcome. It works on the hit and trial method. Once the model is trained than its ready for predicting the new data.

How does it work?
1. At a high level, the machine algorithm creates one model data based on the existing test data as input.
2. Push the new input data then the machine learning algorithm makes a prediction based on the model which was prepared in step 1 above.
3. This prediction is evaluated and if accepted then the algorithm is deployed.
4. If the prediction is not accepted, then machine learning is trained again with bigger training data.

Azure Machine Learning Service –
1. Microsoft Azure provides the cloud-based platform to the machine learning implementation and deployment.
2. Using the Microsoft Azure ML feature, we can prepare data, train the model, test the model, deploy the model, manage and track the model.
3. We can scale out ML to the cloud using Azure ML.
4. Azure ML supports to the open-source technologies like PyTorch, TensorFlow, and scikit-learn.
5. This technology can be used in any ML types which are mentioned above.
6. Use the Azure Machine Learning Python SDK with open-source Python packages or use the visual interface.
7. It has a visual interface for experimenting and deployment with drag-n-drop.
8. Microsoft Azure has Azure Machine Learning Studio to implement, test, train and deploy the ML. Machine Learning Studio is a collaborative place for data science, predictive analytics, cloud resources, and your data meet.

Image Source – Microsoft Docs

Image Source – Microsoft Docs

Conclusion - In this article, we have learned the overview of Artificial Intelligence, Machine Learning, and Azure Machine Learning Service.