How to test data science models acceptability?

Putting a model in production is not only about how many requests per second it can handle

As a manager, you were diligent and you set a data science project running that follows a carefully established strategy. But now, you have a thrilled data scientist who is explaining to you how his/her model has an impressive accuracy with a given validation strategy and you should start to use it in production. Can it be that simple? Read more

Three Strategies Towards Effective Data Science Projects

How to align your data science projects with business needs?

Many data science projects do not go into production, why is that? There is no doubt in my mind that data science is an efficient tool with impressive performances. However, a successful data project is also about effectiveness: doing the right things as Russell Ackoff would write in “A systemic view of transformational leadership”. Read more

Art as a key to AI-driven innovation

AI and data science have ever more applications in our real life, they face major issues when it actually comes to make people use them. Sadly, numerous media push for a fight-or-flight response to AI. Art can be a powerful tool to engage people into its workings and build a positive framework. Read more

Data strategy : helping developpers with AI

Developers and many technical jobs write code for a living. Can you help a developer with Artificial intelligence ? Spending a fair amount of time, conceiving and writing code, I keep falling on the same time-consuming task : debugging and correct typo-like mistakes. Even after close to a decade of code writing, I still keep having these silly tiny mistakes that keep on slowing me down in the development process every once in a while. Read more

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