Machine learning & Deep learning

 

All the solutions you need to engage your customers wherever they are.

While artificial intelligence is the headliner, there are a number of subset technologies which can be applied to solve human problems in many different ways.

Artificial Intelligence is an amazing renaissance to technology, business and society. Machine Learning … will empower and improve every business, every government organization, every philanthropy … basically, there is not an institution in the world that cannot be improved with Machine Learning.

Jeff Bezos, CEO and Founder, Amazon

In an ‘AI first’ world we are rethinking all our products and applying Machine Learning and AI to solve user problems. We are doing that across every one of our products.

Sundar Pichai, CEO Google

What is Machine Learning?

Algorithms that parse data, learn from that data, and then apply what they’ve learned to make informed decisions.

I’m sure you are asking yourself, how can a program or algorithm make decisions and learn from data, doesn’t every program need to be programmed? Not if the program was trained to learn from and adapt to data.

In the case of machine learning the algorithm is not explicitly programmed, rather the model is “trained” using historical and present data in order to make future decisions and prediction. The more data available for training, the more accurate the predictions are. The training of a model involves data scientists scoring algorithms and teaching them to recognise hidden patterns and trends, in order to make accurate predictions. The models learn from new data on a continual basis, enabling it to adapt to the ever changing context and prescribe optimal actions at scale.

Let’s use an image recognition example. Imagine exposing an algorithm to a 1000 pictures of a cat, and letting it determine hidden patterns and features of a cat on it’s own using deep learning. Once the model is trained we can measure statistical accuracy by exposing the model to new and previously unseen images of cat’s, “asking” it to predict accurately if in the image is of a cat or not.

When the model is making predictions with an acceptable level of accuracy, applications and people can use these predictions for decision support. Converting insight and predictions into increased revenue, decreased costs and improved customer experience.

What are some of the low level application for AI and machine learning?

There are three main types of machine learning and each is applicable to a different type of business problem, regardless of industry.

Common use-cases of Machine Learning by functional area

What is Deep Learning?

Algorithm networks capable of adapting themselves to new data.

  • Subset of machine learning

  • Uses a layered structure of algorithms called artificial neural network (ANN)

  • Inspired by the biological neural network of the human brain

  • When trained can learn and make intelligent decisions on it’s own

  • Is usually what is behind the most human like artificial intelligence

The magic of deep learning truly sparked around the year 2010 and has made driverless cars, facebook image recognition and tagging, amazon Alexa speech recognition and various other “human like” behaviour possible, deep learning technology is what triggered the recent boom of AI.

Any organisation which possesses large amounts of data can monetize this data to gain a competitive edge at scale.

We believe that only intelligent enterprises will survive and flourish into the future. There is a need to adopt AI and machine learning to remain competitive.

If your competitor is rushing to build AI and you don’t, it will crush you

Elon Musk

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