Machine learning

Transform the potential of your data into powerful insights to guide development, inform strategy and improve services for your customers.

Machine learning with DoiT

Machine learning is delivering wins across industries, absorbing information directly from data and adaptively improving performance over time. However, harnessing ML successfully can raise significant challenges. Many businesses find that their legacy systems don’t work effectively with machine learning solutions and need to modernize their legacy apps.

Good data and poor data are all the same to machine learning models, so it is important to ensure that the raw data fed into the training dataset is reliable and exhaustive. All relevant stakeholders should be consulted about data acquisition, data preparation and evaluation of results.

Partner with us to leverage our extensive experience, cutting edge technology and passion for machine learning.

Our process

Icon 1 - discovery


We explore your unique business needs and research and prepare data.

Icon 2 - innovation


We’ll help you select features, train your ML model and validate it.

Icon 3 - deploy and optimize

Deploy and optimize

Finally we work with you to deploy and fine-tune your machine learning strategy.

“We want to accelerate service development and delivery, shortening the cycle from data ingestion and model building to production to deliver insights immediately. Google Cloud is the best solution and DoiT is the best partner to achieve that speed and depth we need.”

Jeff McCarrell

Distributed Systems Engineer

Understanding machine learning

Providing a significant competitive edge for many companies, machine learning is a type of artificial intelligence that uses historical data to predict outcomes more accurately. Common use cases include recommendation engines, malware threat detection and business process automation. 

By correlating data with behaviors over time, machine learning algorithms can surface associations and help teams align their products and marketing with customer preferences. It is a key driver for ride-share businesses and many advertisers, for example. 

However, it is not perfect. Machine learning bias can be an issue, with algorithms trained on poor datasets producing inaccurate results. If important populations are excluded from the dataset or the data contains errors, the ML models produced will deliver flawed results, and a business that bases key processes on such biased models can suffer reputational damage – and even regulatory sanctions. 

Major vendors such as Amazon and Google offer a range of machine learning platform services covering everything from data collection and preparation to model building, training and application deployment. 

To learn more about how DoiT can help with your cloud cost optimization needs, click to get in touch.

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