Strategies for Profiting from Machine Learning and Data Science Exploitation

In a series of webinars sponsored by JMP, experts in the field of data science and related disciplines shed light on the current state of big data and data science, revealing that the reality is somewhat different from the initial promise.

The initial promise of big data and data science was to invest in databases and algorithms to gain new insights, potentially reducing the need for subject matter experts. However, as David Hand, PhD, a fellow of the British Academy and a recipient of the Guy Medal of the Royal Statistical Society, and Malcolm Moore, senior technical manager for JMP in Europe, explained, the reality is more complex.

Hand, who has served two terms as president of the Royal Statistical Society and is the author of The Improbability Principle and Dark Data, emphasised the importance of effective data science. He highlighted that it requires communication and teamwork, clarity about what you want to know, a firm grasp of the data, understanding of the quality of the data, and the ability to extract information from data.

Emmanuel Romeu, senior systems engineer at JMP, provided a live demonstration, having previously worked for more than 15 years as R&D project manager for Beckman Coulter and as industrial development manager at Immunotech. Romeu currently supports sales and customer development in France for JMP.

The three speakers of the webinars included Prof. Dr. Klaus-Robert Müller, specialised in machine learning and brain-computer interfaces, Prof. Dr. Sabine Müller, specialised in neurodegenerative diseases and neuroregeneration, and Dr. Tobias Höller, specialised in data science and statistical analysis.

The webinars, titled "Lost in space, found in data: real-world scientific exploration and discovery" and "Building organizational consensus around the tools of digital chemistry", aim to delve deeper into the practical applications of data science and the role of subject matter experts in the field.

In a related news article published on 2022-05-12T14:44:00Z by Katrina Krämer, it was highlighted that yield-predicting AI needs chemists to stop ignoring failed experiments. This underscores the need for collaboration between data scientists and subject matter experts, a theme that resonates with the webinars sponsored by JMP.

Malcolm Moore, PhD, who lectured in medical statistics at Newcastle University prior to joining JMP, reiterated the importance of this collaboration, stating that while algorithms and databases are crucial, they are most effective when used in conjunction with the expertise of subject matter experts.

In conclusion, the webinars sponsored by JMP offer valuable insights into the current state of data science, emphasising the importance of collaboration between data scientists and subject matter experts, and the need for effective communication, clarity, and understanding of data quality in the pursuit of new insights.