Data Science. Physics. Industrial Experience.
What are they? And how do they differ?
Data science is generally understood to mean the analysis of data and the creation of useful insights from combining specific expertise with statistics, mathematics, and programming skills.
Machine learning is a branch of artificial intelligence that aims to fit the parameters of empirical models to a known dataset.
Deep learning is machine learning with neural networks.
A neural network represents a large mathematical equation that describes the connections between input and target variables.
My focus is on working with structured data (databases and tables)
Analysis of process data to improve production yields
Analysis of service data for predictive maintenance
Automated searches for, and classification of, product defects (quality assurance)
Connection of large language models to company data
Evaluation of the company's data for quality and relevance to a selected issue
Advice on which data should be collected and analyzed to create maximum added value
I am a physicist with many years of experience in the analysis and optimization of high-power laser systems. After working in industrial laser R&D for more than 10 years, I am now focusing on data science and deep learning. I am passionate about finding solutions to complex problems.
My broad technical knowledge allows me to generate added value from even small datasets.
I have experience in both data science and practical industrial applications.
Contact me for a FREE initial consultation.
