Machine learning

Empowering organizations with AI

Machine Learning brings a new area of techniques enabling us to solve problems or to implement solutions, previously considered as extraordinarily complex or beyond reach. Equipped with cutting-edge technologies, and driven by business mindset, our engineers apply Machine Learning to help our customers in delivering state-of-the-art solutions, to complete their complicated business challenges and objectives.

We deliver end-2-end Machine Learning projects: from early ideation stages to production of the solution. Thanks to our holistic, iterative, and agnostic approach, our team can assist clients of a wide variety of industries in defining Machine Learning strategies with realistic growth opportunities. Wherever you are in your Machine Learning journey, we can help you move forward in a flash!

The numerous benefits of Machine Learning include

  • Improving bottom line
  • Reducing time and costs
  • Enhancing efficiency
  • Increasing productivity
  • Leveraging new business (product innovation)

1. Forecasting and prediction

Predictive analysis can be used in business to evaluate trends and make estimates or forecasts. By using regression analysis, we can generate insights about consumer behaviour as well as factors influencing profitability, and effectiveness of pricing and promotions of the product from the marketing and sales point of view.

2. Computer vision

Computer vision strives to automate perception and understanding of visual data. This application seeks to develop techniques to help computers see and understand the content of digital images such as photos and videos for the purpose of object detection, image classification, face recognition, and more.

3. Natural language processing (NLP)

NLP focuses on a computer’s ability to interpret human language, in order to process, analyse, and extract meaning from large volumes of natural language text data and speech. Applications range from automated classification, tagging, document or e-mail processing, to extracting information, in order to analyse personality, demographics and mood. With organisations producing more and more unstructured documents, NLP becomes the key to automate their treatment into organized business processes. Through our NLP framework, we can provide exceptionally fast results, building up on our earlier work and research.

4. Recommender systems

A recommender system aims to filter a catalogue of items, to show the end-user the items that are most relevant to them. Applicable in the e-commerce sector (product recommendation), recommenders use can be extended to various business domains. Based on employee’s current job, and job’s history, HR departments can be advised with complete and relevant training plans, tailored for each single employee.

5. Anomaly and pattern detection

Anomaly detection (also outlier detection) techniques detect rare items, events, or observations, that raise suspicions by differing significantly from the rest of the data. By identifying, monitoring, and recommending counteractions, Machine Learning helps businesses respond to anomalies in no time.

Machine Learning can also be used to identify clusters of objects that are in some ways, similar to each other, allowing to detect common patterns, propose their segmentation, etc. Both these are key tasks of exploratory data mining.

How we work

We deliver value to you at each step of a standard Machine Learning workflow. Our way of work is highly iterative. We frequently gather feedback from business stakeholders, to make sure that parameters of the project and business objectives are aligned and enhanced with each iteration. The process always involves at least 7 steps:

  1. Business analysis

First, we help you to define the problem that you want to solve with the help of Machine LearningThen, we determine the data and the model to be used, and the expected results.

  1. Team and process definition

Together with you, we set the right targets to be reached. Then, we align to set up the right project team and the right stakeholders for achieving your Machine Learning objectives.

  1. Data exploration and preparation

The quality of your input determines the quality of your output. Thus, we explore, transform, and enrich raw data into clean and structured formats. Then, we construct the data sets. This step is critical to avoid unexpected problems during the next phases or the project.

  1. Model development

The next step in our workflow is to choose and develop a high-performance Machine Learning model.
We perform this step carefully and methodically, so that it delivers the return on investment that you expect.

  1. Deployment at scale

In this step, we deploy the best model and data transformation to your production environment. We then use it to make predictions from real and continuous data.

  1. Monitoring

To ensure that the Machine Learning models overcome unexpected issues and are effective in their performance, we constantly monitor the models and refit them over time.

  1. Continuous training

Continuous training is an automated system to continuously evaluate and retrain your Machine Learning models to keep them up to date. To this end, data is continuously used to extend the existing model’s knowledge.

From model building to operating in production

  • MLOps

DevOps has become standard for IT operations and Cloud services. Since there is powerful synergy between DevOps and Machine Learning, we can bring the lifecycle management of DevOps to Machine Learning for its greater benefit.

This way, DevOps / Machine Learning lifecycle management emphasizes on process and automation and fosters a culture that encourages new ways of working together across teams.

  • FinOps

ML projects can require extensive computing resources. In synergies with our Cloud Center of Excellence, we promoted a cloud-first approach for ML project in which we optimize the resources costs at every step.

Customers with a private Cloud solution also benefits from our approach to define and tune the infrastructure requirements of their ML projects.

Contact us for free ideation workshop

Do you want to introduce and leverage Machine Learning in your organization quickly and effectively? If so – contact us for a free ideation workshop, designed exclusively for your organization to discover where Machine Learning can take you!

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