Get acquainted with the essentials of Scikit-learn in this part one workshop of Track 4: Scikit-learn led by Francesco Mosconi, who will teach you how to build regression and classification models with Scikit-learn, evaluate model performance and select the right techniques & tools, before jumping into practical, hands-on tutorials in part two.
In this workshop, you will learn:
- Recognize problems that can be solved with Machine Learning
- Select the right technique (is it a classification problem? a regression? needs preprocessing?)
- Load and manipulate data with Pandas
- Build regression and classification models with Scikit-Learn
- Evaluate model performance with Scikit-Learn
Level:
Beginner - Intermediate
Prerequisites:
What you should know (or have pre-installed) to get the most value.
- Anaconda Python 2.7
Meet Your Instructor:
Francesco Mosconi | Data Scientist | Catalit LLC
The course is lead by Francesco Mosconi. Ph.D. in Physics and Data Scientist at Catalit LLC, he was formerly co-founder and Chief Data Officer at Spire, a YC-backed company that invented the first consumer wearable device capable of continuously tracking respiration and physical activity. Machine Learning and python expert he also served as Data Science lead instructor at General Assembly and at The Data incubator.
