Blog - Page 23

Data Science22 Jan

Practical Tips for FMCG Companies Adopting MLOps. A Guide for Programmers

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

Jakub Grabski

Generative AI22 Jan

Privacy and Data Security Challenges in the Era of Large Language Models (LLMs)

LLMs bring new privacy and data security risks, from data leakage to bias. How tokenization, differential privacy, and secure handling protect your data.

Krzysztof KacprzakChief Technology Advisor

Augmented Reality22 Jan

Progressive Web Applications

A PWA is a web application with the features of a mobile app. What progressive web applications are, their key traits, and why businesses adopt them.

Marcin KozłowskiAI & Cloud Solutions Director

Data Science22 Jan

Prospecting Ideas Using Data Modeling

Data modeling can support sales in B2B and B2C by finding high-value prospects and predicting customer behavior. The key data science techniques explained.

Dawid Kamrowski

Data Engineering22 Jan

Real-Time Big Data Analytics: Examples and Benefits

Real-time big data analytics explained: how instant processing improves decisions and fraud detection, which industries use it, and what it delivers.

Laura Kszczanowicz

Data Science22 Jan

Relational vs non-relational databases – a comparison

Choosing between SQL and NoSQL? Compare relational and non-relational databases and see which type fits the software you plan to build.

Pawel Jedrzejewicz

Artificial Intelligence22 Jan

RoBERTa vs BERT: How Transformer Models Evolved

RoBERTa vs BERT compared: see how their architecture, training, and performance differ, and which transformer model fits your NLP project best.

Krzysztof KacprzakChief Technology Advisor

Generative AI22 Jan

RoBERTa vs GPT-4: A Comparative Analysis of Language Model Capabilities

RoBERTa and GPT-4 differ in architecture, training objectives and use cases. See where each language model fits, from text classification to generation.

Krzysztof KacprzakChief Technology Advisor

Data Science22 Jan

Stateful vs. Stateless architecture – which solution is better for your application?

Stateful vs stateless architecture compared, with the pros and cons of each approach to help you pick the right one for your business application.

Tomasz Stachera

Data Engineering22 Jan

Strategize for Success: Implement Automation to Boost Productivity

Business automation depends on data engineering. How pipelines, analytics and integration feed automated processes, with practical steps to get started.

DS Stream

Data Science22 Jan