Section1 - Chapter2:- Machine Learning for Cyber Security

Section 1 - Chapter 2:- Machine Learning for Cyber Security

* Introduction :- Intro to Machine Learning and Cyber Security
* Section1-Chapter1 :- ML Development environment using Docker, Conda, Jupyter Notebook , Kubernetes, Intellij etc.
* Section1-Chapter2 :- Feature Extraction, Dimensionality Reduction, Data Labelling using Unsupervised Learning .
* Section1-Chapter3 :- Supervised Learning (Malware Classification), Classification model comparison.
* Section1-Chapter4 :- AutoML Frameworks (H2O autoML)
* Section2-Chapter1 :- Machine Learning with Apache Spark on Kubernetes .
* Section2-Chapter2 :- End to End ML Pipeline using Apache Spark using Jupyter Notebook(s)
* Section2-Chapter3 :- End to End ML Pipeline using Apache Spark using CI/CD approach
* Section2-Chapter4 :- Integration of XGBoost and H2O autoML with Spark.
* Section2-Chapter5 :- GPU accelerated training using RAPIDS (a cuda framework based software)
* Section2-Chapter6 :- Deep Learning using Tensorflow/Keras on GPU
* Section2-Chapter7 :- TBD.

Here we will also do the Feature Extraction and Data Labelling on our Raw data , and to do that we will follow these steps in an order .
a) Import and load the raw data
b) Feature extraction from raw data
c) Feature normalization
d) Clustering and labelling the data
e) Data visualization
f) and finally saving the labelled data for future use cases.


Contact Me

LinkedIn :- https://www.linkedin.com/in/shaileshp...
Gmail :- [email protected]

Links discussed in the tutorial

GitHub :- https://github.com/ez-ml/ML-For-Cyber-Security
Docker Desktop :- https://docs.docker.com/desktop/
Kubernetes Kubectl :- https://kubernetes.io/docs/tasks/tools/install-kubectl/
IntelliJ IDEA :- https://www.jetbrains.com/idea/download
Docker Hub :- https://hub.docker.com/
Docker best practises :- https://docs.docker.com/develop/develop-images/dockerfile_best-practices #dockerfile-instructions

1) Download the dataset from following link .
Dataset :- https://drive.google.com/drive/folders/1jsQPWKxe8ql2EcpSGXP7_6nXYRyB0zv-

Please comment in an underlying video with you email address, and i will share the given dataset with you .


2) Docker commands discussed in the tutorial
1) #Run the docker image 2.
docker run -p 8888:8888 ml-image-2:latest