Latest blog posts by Jakub Grabski

How data science and advanced analytics turn raw data into better business decisions, with steps to build a data-driven strategy and the tools involved.

Cloud vs traditional IT: why businesses move from on-site servers to the cloud for flexibility and lower upfront costs, and what to plan before migrating.

Machine learning in predictive analytics turns raw data into reliable forecasts. See how models anticipate demand, churn, and risk before they happen.

Practical MLOps tips for programmers at FMCG companies: start with pilot projects, invest in training, build team collaboration, and automate workflows.

ML as a Service (MLaaS) lets teams build supervised learning models without heavy infrastructure. See how it speeds deployment and lowers project cost.

How FMCG companies apply CD4ML, continuous delivery for machine learning, to ship ML models safely and often, with best practices and case studies.

MLOps brings DevOps practices to machine learning. Its core components and how FMCG companies apply them to demand forecasting, inventory and marketing.

MLOps in FMCG supply chains: automating the deployment, monitoring and management of ML models, with the key tools, best practices and results to expect.

MLOps in FMCG: how automated ML deployment and monitoring support demand forecasting and inventory management, with key tools and practical examples.

MLOps tools for FMCG developers: how TensorFlow, Kubernetes, MLflow and Kubeflow automate machine learning workflows, with tips on integration.