machine learning

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Machine learning is a set of artificial intelligence techniques that gives web and mobile applications the ability to learn, adapt, and improve over time. It does this by processing vast amounts of data, identifying trends and patterns within it – most of which would not be apparent to a human being – and then making decisions and taking actions to help meet specific objectives. 

 The use of machine learning (ML) in business is increasing rapidly. Smart companies are harnessing the value of their data in machine learning models to reduce costs, optimize processes, and increase customer satisfaction. AI and ML have the potential to reshape industries – ML algorithms can be used in applications across practically all sectors, from eCommerce to finance, healthcare to education, and cybersecurity to digital marketing.

Our developers are open source contributors with more than 220 repositories on GitHub. We constantly invest in developing new digital technologies and testing solutions in our R&D department, sharing our experience and expertise both on expert blogs and at various tech industry conferences. Our team has provided machine learning services in a variety of engagements, including many end-to-end projects. 

There are a variety of machine learning solutions that can be tailored to different business needs. To make sure you get the most out of your project, our data science experts will select the best approach for the specific needs of your business and your market. 

• Data Engineering - prepare your data to make the most of AI algorithms
• Data Science - uncover meaningful insights to improve your product or service
• Recommender Systems -  create a personalized experience for every user thanks to an accurate recommendation system
• Natural Language Processing - build natural interactions with your users and reconize patterns in unstructured data

 Over the years, our team has tested and implemented a transparent and efficient workflow for machine learning projects. Our processes ensure our customers receive more reproducible results faster and in a more flexible way.

Our workflow focuses on three stages: 

1. Data mangement - we ensure that we have everything the model will need during training
2. Model flow - we create a model capable of producing predictions
3. Deployment - the model is connected to your application
4. Ongoing maintenance of model with updated data