#ml-bootcamp Machine learning bootcamp for ICN Singapore
The goal of the bootcamp is to make our team familiar with the basic concepts in machine learning and make them comfortable with the basic vocabulary of machine learning.
At the end of the bootcamp, everyone in the team should be famiiliar with the following concepts
- Machine learning
- Deep learning
- Supervised / unsupervised learning
- Classification, regression, clustering
- Training / testing of machine learning models
- Feature engineering
- Building and integrating a machine learning pipeline
- Feel confident about ML
- Minimal slides (10-20 slides per presentation), put emphasis on hands-on experience
- No talk longer than one hour
- Do not use too many different frameworks and tools, stick to Python/scikit-learn/Theano
- Redundancy is good
- No hackathon challenge, will be too challenging for the first bootcamp
- Example 'hello world' code examples
- 'Batteries included': all examples work out of the box
- No installation: all examples will be available on Jupyter hub, just bring your browser
- Github is single source of truth: everythin is on github: code, examples, solutions, documentation, slides
- Extensible: participants can continue after the bootcamp
- Do not talk about Big Data, Hadoop, etc.
Important: participants are not required to clone this repository to their own PC. All excercises/tutorials are carried out on Jupyter Notebooks, which allows live interactive coding with documentation on a web environment. Participants don't need to install any software before the bootcamp.
- Connect to Corporate Wifi Network.
- Open your favorite web browser and go to http://lssinh003.sin3.sap.corp:8000/hub/
- Login with username your own i#(start with capital I)
- Click
newbutton at the right corner and selectterminal, typecd ml-bootcamp; export GIT_SSL_NO_VERIFY=1; git pull.
You should be able to see ml-bootcamp folder after login. In the folder you will find all the notebooks you need for this bootcamp.