Data Scientist – Director of the Data Science & Customer Intelligence offerings at Business & Decision France. Also teaching Data Mining & Statistics applied to Marketing at EPF Schoolg and ESCP-Europe.
All posts from Didier Gaultier
AI Industrialization: the key steps to a MLOps approach
The industrialization of artificial intelligence - one of the 7 hot data topics for 2022 requires the implementation of MLOps. This approach includes some necessary steps, including a common platform...
WHITEPAPER | Data Ethics/AI Ethics: the 2 faces of a responsible future
Artificial Intelligence is at the heart of all attentions and concerns right now. Did you know that the real difficulty with Artificial Intelligence is not the algorithms, nor the design...
WHITEPAPER | Artificial Intelligence: Stay in control of your future!
If there is one topic that really ignites passion and fuels all ideas and discussions in the world of new technologies, it’s Artificial Intelligence. What are the opportunities for enterprises?...
Statistics versus Machine Learning: should they really be opposed?
This "seemingly" old debate deserves to be revisited with fresh perspective. Data Science (such as Big Data) is a constantly evolving field with nowadays proven applications namely in the fields of customer knowledge and marketing… Statistics...
The 5 key Data Science practices
In the wake of Big Data, many companies embarked on the Data Science journey, the field having established itself as the inescapable route towards Big Data transformation into knowledge and...
Can a whole Data Science project be done using R or Python?
For several years now, many Data Scientists have found themselves turning to "language" command line tools, such as R and Python, to deal with Big Data. But can you really undertake a whole Data...
The key to Data Science success is the CRISP methodology
The CRISP methodology (originally known as CRISP-DM), first developed by IBM in the 60s for data mining projects, remains, today, the only truly efficient process used for Data Science projects… CRISP methodology: User guide The CRISP methodology includes 6 steps that range from business understanding to deployment...
Data Scientist/Data Engineer: the skills required to give you a head start in Data Science
Back in 2012, the Harvard Business Review published an article with a somewhat revealing title: "Data Scientist: The Sexiest Job of the 21st Century". Years later, we revisit this vision...
Data Engineer: which training programs to choose?
To all those young people wishing to embark on a career in Data Science, my advice was to begin with a Data Engineering job rather than directly as a Data...
Artificial intelligence, machine learning, data science: are these terms interchangeable?
Many writers talk about AI, machine learning and data science, as if these terms were broadly interchangeable. What’s going on exactly?