Machine learning for cyber security is one day hands on training session to be conducted at Seasides. This training is crafted for students and entry level industry professionals who are interested in machine learning to understand cybersecurity risks and tools/techniques that can be used to mitigate those risks.
This training does not require prior knowledge of machine learning. But it is expected to have basic python programming knowledge. Training will cover basics of machine learning including supervised and unsupervised machine learning. It will also cover real world case studies related to cyber securi
Content:
- Data manipulation using Pandas
- Introduction to machine learning
- Introduction to supervised machine learning
- Logistic regression
- Decision tree
- Random forest
- K nearest neighbours
- Introduction to unsupervised machine learning
- Dimension reduction
- Clustering
- Introduction to neural networks
- Introduction to natural language processing
- Case study – detecting malicious URLs
Target audience This session is a basic introduction to machine learning and its use cases in cyber security. This workshop is targeted for students and entry level professionals with interest in machine learning and its applications in cyber security
Requirements A laptop with Python installed (You can install it using Anaconda distribution - https://www.anaconda.com/products/distribution )
Key Takeaways:
- Data manipulation in Python
- Machine leaning basics
- Identifying cyber security where machine learning can be used
About trainer
Bhaskarjit Sarmah is data scientist at BlackRock. His work mainly focusses on building machine leaning solutions for trading and risk management. His research interest includes explainable AI, network science, model uncertainty to name a few.
Bhaskarjit Sarmah is one of the top instructer at Udacity and Coursera learning platform and program mentor at MIT Machine Learning course.