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
Discovery
We explore your unique business needs and research and prepare data.
Innovation
We’ll help you select features, train your ML model and validate it.
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 at no extra cost, click to get in touch.
Related resources
Lessons from an AWS Migration Acceleration Program member
AWS Partners who achieve MAP Competency status must prove exceptional expertise and success in helping customers with their AWS migrations. We offer valuable insights into how we did it.
Create technical documentation that works
Technical documentation in the high-tech industry is often dismissed as an add-on. We explain how you can use it to bring true value to the product.
Align your app modernization with cloud-native design principles
Monolithic legacy systems can hinder your competitive efforts. An app modernization strategy entered on cloud-native architectures enabled by containerized workloads will ease the path to success.
