In this hands-on workshop, participants will learn the fundamentals of machine learning through practical experience with the Titanic dataset. By the end of the session, you will be able to:
- Understand the basic concepts of machine learning.
- Apply machine learning algorithms to real-world data.
- Evaluate the performance of machine learning models.
- Collaborate with a team to solve machine learning problems.
- Ensure that git is installed on your machine. Download Git.
- Basic programming knowledge (Python recommended) Download Python.
- Familiarity with Jupyter Notebooks.
- Clone the repository.
git clone https://github.com/CogitoNTNU/course-on-machine-learning.git- Install juptyer notebook
pip install ipykernel -U --user- Team leads should join Kaggle and create a team. Join Kaggle Competition
Follow the parts in order, completing tasks and exercises as you go. Experiment with the code cells to reinforce your learning. Refer to the "Extras" section for additional tools and techniques beyond the course scope. Happy learning!
The Leaderboard shows the final results of the competition.
This workshop is based on the Titanic: Machine Learning from Disaster competition on Kaggle.
Many thanks to our amazing CEO Olav Selnes Lorentzen and our talented Ksenia Mordovets for their contributions to this workshop and making the presentation slides so beautiful. Thanks to Professor Zhirong Yang and Ryutaro Tanno insights.
 Sverre Nystad |