The way businesses use data determines their degree of success. Gathering lots of data from web analytics, customer demographics, purchase behaviour and systems are on their own not being particularly helpful. In fact, 90% of data within organisations are unstructured and messy. Finding relevant insights into data and applying machine learning to those data enables companies to truly optimise their processes, react to their customers' needs proactively and become significantly more competitive.
With the evolution of computer systems, an increase of cloud-based capacity and computer power machine learning has become much easier for companies to use. Google Cloud AI provides modern machine learning services, with pre-trained models and a service to generate your own tailored models. The neural-net-based machine learning service has better training performance and increased accuracy compared to other deep learning systems. Google's services are fast, scalable, and easy to use.
Let's say we have thousands of car images and we would like the computer to define the type of car and return it as a text output. To start with, we can train the computer to predict the outcome using a machine learning model using and lots of data and examples.
The picture consists of a big amount of data (pixels) but the computer does not know how to interpret them. The data of the image is being analysed by the computer a transformed step by step into a feature representation. Starting with the low-level features such as light and colour, then medium-level features looking at small parts such as the wheels of the car, to high-level features which are related to the car. Based on the feature representation the machine is able to predict an output.
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