Our first Machine Learning weekend

The first Data Weekend on Machine Learning in San Francisco was a great success!

Participants arrived in the morning, not sure of what to expect. After all they were the pioneers... The first curious ones wanting to spend a whole weekend cranking on Data Science.

We mingled over breakfast and participants started to get to know each other and interact, then at 9:30 we started to work.

During the first day participants discover the basic techniques of Machine Learning: regression, classification and clustering and they learn to apply them to data problems using Python. The balance of class to theory is about half and half, so that one builds knowledge and hands-on practice together. Real world datasets are used throughout the examples, starting from simple and then building up complexity.

We had breaks for coffee and lunch. It was very hard to break sessions, though. People seemed to be genuinely engaged and having fun learning, so much so that they were willing to skip coffee breaks and lunch !

On the second day the atmosphere was more relaxed and familiar. People were getting to know each other, and we facilitated that with a short fun activity in the morning. Then, more advanced techniques were introduced. Students learnt how to validate a model and how to judge the results of a prediction task. The whole afternoon of the second day was dedicated to the final project, which involved setting up a simple website to serve predictions based on a model.

When the second day was over, we parted with a smile. The experiment was a success. Data Weekend was born!

Read the comments of people who participated:

A very good introduction, which provides a map of the field, a theoretical explanation and useful tool to start experiments on your own.
— Raffaele
A crash course on data science with real exposure to coding and a valuable and interesting final project.
A very well structured flow of the course with a great final project!
— Dimitar
Best way to get started in ML coming from a techie position.
What stood out the most for me were the programming exercises! They were well-designed, 1-page data science Python programs that I could understand by reading quickly and then working on improving or extending in some well-defined way. I feel much more comfortable with Python’s data science libraries now!
A very good introduction, which provides a map of the field, a theoretical explanation and useful tool to start experiments on your own.
A crash course on data science with real exposure to coding and a valuable and interesting final project
Most productive weekend in my last few years :)

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