End-to-end ML for real-world applications
Most Machine Learning courses are given from the perspective of a Data Scientist and focus on the techniques and algorithms that allow to learn from data. This workshop takes the perspective of an application developer and instead provides an end-to-end view of ML integration into your applications. We’ll go all the way from data preparation to the integration of predictive models in your domain and their deployment in production.
The right mix of theory and hands-on work
The workshop is agnostic and features the best open source Python libraries (Pandas, scikit-learn, SKLL), APIs and ML-as-a-Service platforms (Microsoft Azure ML & Cortana Intelligence Suite, Amazon ML, BigML) for developers getting started in Machine Learning. It focuses on only two learning techniques, which turn out to be the most commonly used in practice: decision trees and ensembles.
Each workshop is 2 day long and comprises 8 modules of 3 blocks of 30’ each—including time for questions. Blocks are either Theory or Exercise, with at least one Exercise per module. The goal is to make you operational with machine learning at the end of the workshop.