Machine Learning is becoming a reality with more businesses getting a handle on how to leverage it and demonstrating its benefits with effective deployment. This has been possible due to the growth of cloud computing which has provided cheap access to vast processing capabilities, even to small enterprises. Combined with the easy availability of sophisticated open-sourced frameworks, machine learning has arrived to dramatically impact business landscape forever.

Machine Learning is the form of data analysis that enables to automatically detect patterns in data and use them to make predictions for new data points as they become available. Thanks to Machine Learning, businesses can build smart applications to predict challenges, forecast demand and anticipate change in customer behaviour, equipping them to be better prepared with proactive measures and build capabilities to respond with a winning strategy.

Machine Learning provides the next level of insight from data. For example, based on what the business knows about the user, machine learning will enable business to predict more accurately what the customer will like or purchase.

The possibilities of Machine Learning is infinite—from recognizing faces to detect crime or recognize customer frustration; matching resumes for appropriate hiring and managing attrition; designing marketing campaigns, personalizing offers, designing web pages to detecting earthquakes, floods and storms its application encompasses all aspects of human existence.

The service offerings from AWS have uniquely evolved to form a comprehensive offering to leverage machine learning at scale. A host of services including Amazon Redshift, RDS, S3 and EMR offer retrospective analysis and reporting; while Amazon Kinesis, EC2 and Lambda enables real-time processing and dashboards—businesses using all/some of these services can easily leverage machine learning by using Amazon supervised learning algorithms for exponential business advantage.

So how can you get started? First, since data is the key to machine learning performance, the more data you have is better. Focus your efforts towards building high-quality data sets, which is the hardest.

Next explore and understand your data. Machines Learning will throw up patterns and provide insights into what the pattern is. Asking the next level of questions and finding co-relations is the role for humans and very specific to business goals and requirements.

This means businesses will have to evaluate and explore model performance to generate predictions, while constantly iterating and refining these models to the get answers, aligned with changing business goals.

While Machine Learning relies a lot on automation and self-learning, the role of humans will grow critical as extracting and curating, and decisions regarding which data sets to leverage for what outcomes will continue to rest on humans. Machine Learning presents new opportunities for human and machines to collaborate and push the frontiers to make winning easier, faster.