CategoriesAbout the course
After a fair amount of pedagogical and technical preparation work, five core developers and members of @scikit_learn will guide you in predictive modeling with the use of the scikit-learn Python library!
The aim of the course, provided only in English, is to teach how to use scikit-learn, but also to be critical about each step of the design of a predictive modeling pipeline: from choices in data preprocessing, to choosing models, gaining insights on their failure modes and interpreting their predictions.
The course covers practical aspects through the use of Jupyter notebooks and regular exercises. Everything is integrated in the course and you don't have to install anything. Step-by-step and didactic lessons introduce the fundamental methodological and software tools of machine learning.
Predictive modeling is applied to a wide variety of data, from business intelligence to industrial processes and scientific discoveries. Our learning approach is to make machine learning accessible to a wide audience, without a strong technical background.
This course features a forum to share your questions and experience in data science with teachers and other participants. It provides an opportunity to expand your network with machine learning fellow learners and experts. Join now the +10,000 members of the #ScikitLearnMooc community!
Enrollment: From Sep 18, 2023 to Oct 30, 2024
Course: From Nov 08, 2023 to Nov 07, 2024