Hello everyone,
I'm starting the implementation phase of my research thesis which is about phishing detection using deep learning.
I'm new to this, but I've already selected features that are mentioned in other literature. However, after doing a bit of research I became confused if I could do manual feature extraction and selection or not.
Some answers that I've found say that what distinguishes machine learning and deep learning is that deep learning does the features extraction automatically during training, is this true?
Also, I'm planning to use python for implementing this solution, if you have any suggestions for any tools or libraries that could help me in this matter it would be helpful.
thanks in advance.
Hi,
These are two codes ( python and R )
Code Deep sparse denoisig with DNN (R code )
https://www.researchgate.net/profile/Muna_Al-Hawawreh/publications
To understand how deep learning deal with features..this paper will help you.
Conference Paper Leveraging Deep Learning Models for Ransomware Detection in ...
Good luck
It is not useful because of more wasting time. The computer can do this operation with much smaller time than the use of manual extraction.
You can do it for study examples purposes, however., for large examples it may be a waste of time. The modern computer based computing are mainly for time saving and quick results. For understanding such concepts, you can try small examples manually in basic text books. See e.g.,
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