Machine Learning with AWS
‘Big data’ is big; unfortunately many organisations struggle to wade through the masses. Computing these days is such that countless organisations easily collect masses of undistinguishable data, which potentially could be used to add value in many ways. What isn’t as easy is analysing this data, this is more convoluted and requires the right skills and tools.
Google, IBM and Microsoft Azure offers services of sorts to help with this and now Amazon has followed suite with the AWS Machine Learning service.
Big data is everywhere; there is no escaping it. The wealth of information companies are able to collect these days and with such ease is mind-boggling. Many organisations have found themselves in the situation where they have accumulated mounds of data and know this data has the potential to be valuable but they haven’t the foggiest of how to go about analysing it. They do not have the expertise on hand and acquiring them comes at mostly high cost and the challenges still remain.
Data analytics has taken up an important place in present day and future IT. Companies such as Google, IBM and Microsoft have an offering for this purpose and now Amazon has an offering too- the Amazon Machine Learning Service. With this service AWS customers can take advantage of the service to analyse their data without the requirement for the expertise and the tools.
Developers make up a large portion of AWS’s customer base. The ability to include machine-learning capabilities into the applications that they develop is greatly advantageous. This is usually a challenging feat for the developer and one that is not often accomplished; as the procedure requires many skills (statistics, data analysis and machine learning skills), moreover conventional methods are extremely labour intensive and time consuming. An automated, easy to use approach and far reaching alternative is required and thus Amazons Machine Learning service has come about.
Many large companies are using and have been using Machine learning capabilities for some time, allowing them to match products with customers for example, now individuals and smaller companies can take advantage of the benefits from data analytics as well. With being able to analyse and utilise the data that they accumulate they can gain an awareness that otherwise may never have deliberated.
What is Machine learning and why is it necessary
Machine learning encompasses the creation and study of algorithms that can learn from data and make predictions on data. It progressed from the study of pattern recognition and computational learning theory in artificial intelligence.
Machine learning has been further developed to assist people and organisations and is heavily relied upon by organisations that are data-driven. These smart systems usually work behind the scenes, with many of us unaware. Majority of us utilise it on a daily basis without even realising it.
Algorithms analyse and learn from the data so that the services delivered or offered can match the requirements best.
For organisations machine learning is fundamental, for a simple and cost effective approach for analysing of Big Data. With machine learning tools, organisations no longer need to rely on data analysts to do the arduous task as machine learning does a more effective job, with more accurate results and in a fraction of the time.
Machine learning within a business environment takes decision making to another level, to decipher a broad range of problems. Machine learning can assist with fraud detection, monitoring, forecasting, customer-targeting and product recommendation, to name a few.
It also opens up the world of data analytics to more businesses and individuals that otherwise would not have had access to data analytics.
Some advantages of machine learning in the cloud
- Traditional labour intensive analysis is now automated
- Reduced cost for analysis of data
- Reduced time taken to analyse data
- Masses of data can be analysed more efficiently with greater accuracy
- Accuracy is often enhanced compared with a manual approach
- Faster and higher throughput
- Refines disorderly and diverse data into a relevant arrangement of data to enable optimised decision making
- Can be engineered to automatically and continuously learn from new data
- Improved scalability
- Drives competitive advantage
- No need for hardware, procurement or set up
The Amazon Machine Learning Service
Amazon has accumulated extensive proficiency and knowledge in machine learning over the years, utilising its capabilities successfully throughout its online retail business. Using this extensive knowledge to develop a completely managed machine learning service to be utilised in the cloud.
The service is directed at the developer/user of the Amazon cloud and enables easy sort through and analysis of data stored in the Amazon cloud, to make both batch and real-time extrapolations, allowing the developer/user to build predictive applications with ease.
Utilising the Amazon Machine Learning service, anyone can make sense of their data without the need for an analyst, tools, and specific infrastructure to support it all. All these barriers no longer exist. The service is pay-as-you-go as with the other AWS’s, with no set up costs involved hence even the small business or individual can benefit.
The service is easy to use and follows a step-by-step guided approach that’s easy to follow, even if you are not experienced in the area at all.
What it supports
Three types of analysis are supported by the service and can be run against data to produce multiple models:
- Binary classification (predicts one of two potential outcomes)
- Multiclass classification (predicts one of three or more potential outcomes)
- Regression (predicts a number value)
The models can then be used to classify data uploaded from stored batch data or real-time data.
Multiple models can be developed using the Machine Learning console and application programme interfaces (API).
How it works
Amazon Machine learning service applies algorithms that can assist the user to create machine-learning models. Through training data initially, patterns can be uncovered in existing data and can be utilised to make predictions from new data in batch mode or real-time as chosen. Once the user has built the model, adapted it and fine-tuned it to their requirements and is satisfied with it, predictions can be made at scale.
The service is integrated with Amazon Simple Storage S3, Redshift and Amazon RDS, utilising data already stored in the Amazon cloud.
Amazon Machine Learning console and API
Developers can use the application programme interfaces (APIs) to include machine learning into apps and aids in sidestepping the requirement of coding algorithms into the software.
APIs are provided for generating, linking with and influencing data sources, models, predictions and evaluations. They provide data and model virtualisation tools to help with quality evaluations and assist with making adjustments to predictions so that they best match the intended purpose.
The Amazon machine learning console and API allows for:
- Ability to speedily create multiple models if required
- High throughput of data for enhanced prediction generation
- Heightened scalability
- No concern of management and monitoring of the infrastructure as this is part of the service
It’s important that businesses of all sizes can take advantage of machine learning capabilities. In the data-driven economy being able to use the masses of data collected to assist and enhance business function is essential and helps in maintaining a competitive advantage.
Amazon machine learning provides its users with a service to help them make better use of their data. This cloud-based service opens up the possibilities of machine learning to a broader continuum at reduced expense, time and effort.
The service is based on Amazons own accumulated experience and deep-rooted in their success of utilising machine learning in their business themselves.