Example ML use cases

Improve users' experience by observing behavior and predicting needs/interests
Exploit the value of customer data: predict churn, upsell opportunities, revenue, and optimize offerings
Save time by automatically categorizing documents and prioritizing tasks
… and more covered in the book!

Start your own ML project

The book teaches you what makes ML work and what are the limitations, so you’ll be able to develop your own original ideas of ML applications. You’ll learn how to incorporate domain knowledge into your ML system, and how to create value from predictions.

Use ML-as-a-Service

While others are investing time and money to build their own ML algorithms and infrastructure, you can be much quicker by adopting Predictive APIs and ML-as-a-Service. Bootstrapping Machine Learning teaches you how, so, you can focus on the most critical aspects for the success of your project: preparing data and acting on predictions.

Hi! I’m Louis, as an independent consultant and ML specialist, I help corporations and startups integrate ML into their products. I have held workshops at major companies such as Amazon, Deloitte, EDF, Intel, Konica Minolta, and I have coached smaller businesses and growing startups in their usage of ML. I’ve been working in ML for more than 10 years and I hold a PhD from University College London.

I’m the author of Bootstrapping Machine Learning and of the Machine Learning Canvas. I’m also General Chair of the PAPIs.io international conferences, Adjunct Teaching Fellow at UCL School of Management, and board member at France is AI.