Data Analysis & Machine Learning
In the previous post “Getting Started with Machine Learning on Azure”, we learnt about what’s machine learning, the reason we must know about it, how it benefits us in long run and little touch on Azure Machine Learning. So, today, we are going to discuss about Azure Machine Learning. But before that, let’s talk little bit more in data analysis so we know about how machine learning evolved from ancient statistic to where it is today.
Introduction to Data Analysis
Data Analysis is actually not a new thing. It was evolved from statistics which has a long history, and growing more important when amount of data is increasing.
Interestingly, I found there is an article that said the starting of statistics or data analysis could be traced to an ancient Egypt when Egyptians was trying to use period census to build the pyramids.
Over the time, with more data is being collected, analyzing data became a process to identify the key information that will benefits businesses, governments, financial institutes, and even individuals.
Data Analysis to Machine Learning
Even though data analysis can be done by human, but it requires a lot of time, cost and human efforts. In 1950, Alan Turing conducted a test named “Turing Test” to fool a human into trusting that it is also a human. Further then, Arthur Samuel who was a pioneer of computer games and AI, wrote the first computer self-learning program to study strategics of playing checker game.
In 2010, Microsoft Kinect able to track 20 human features at 30 times/sec to learn & identify the human movements and till recent years, personal assistant bot like Cortana made the change where it can interact more and naturally with people. Today, Machine Learning became a key using data statistics to unleash many possible solutions to our society’s problems, such as auto-pilot cars or identify emotions to predict criminals.
Machine Learning Allows App Gets Smarter Over the Time
By continuously learning from the existing and new data, the machine learning allows your application gets smarter and smarter over the time. It can predict more accurately, identify purposes more precisely and it keeps learning by itself.
What Can Azure Machine Learning Do for Me?
Azure Machine Learning consists of Cognitive Services, Azure Machine Learning Studio and Azure Machine Learning Workbench. They provide different level of customisability and extensibility.
Cognitive Services which has been discussed in our previous post here, is suitable for the developers who just want to focus on their client app development instead of writing the intelligent algorithm.
Then followed by Azure Machine Learning Studio which we will talk about its implementation today, that will have Web Portal to provide you simple drag and drop functionalities. Last, Azure Machine Learning Workbench is for those Data Analysts, Data Scientists or developers who are heavily focus on creating their own algorithm from zero.
Why Azure Machine Learning Studio?
Azure Machine Learning Studio provides the benefits such that it is fully-managed, simple yet having the best-in-class algorithm and it is easy to deploy and setup as a web service! Everything is on Azure cloud reliable and secured environment!
The following picture also gives a glance that how we will proceed from the beginning to the end when we use Azure Machine Learning Studio. As you can see, it is as simple as 6 major steps only.
What are the Supported Data Source?
The supported data sources by Machine Learning Studio range from Azure Blob Storage, Azure SQL DB, popular Hadoop Hive Query, CSV, or from other Web API.
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