- Why we are interested in Machine Learning.
- Introduction of Machine Learning.
- How to get started Machine Learning.
- Types of Machine Learning.
- Datasets Collection.
- Datasets Preprocessing.
- Machine Learning Algorithms.
- Environment Setup.
- Research vs Production.
- Data pipeline.
- Live Code & Example.
- Deployment.
- Clone this repository.
- Without temparing with the data i.e. leaking train data to test data, build a CNN model. (Refer to day 2 recorded video)
- Conditions: The model must achieve accuracy of 85-90% in classification report when epoch=10.
- Submit the notebook to any of the speakers