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Name: JAYDEEP TADHANI
Type: User
Company: JTACADEMY
Name: JAYDEEP TADHANI
Type: User
Company: JTACADEMY
:octocat: Machine Learning for Cyber Security
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
Darknet traffic time series analysis using Machine Learning techniques like LSTM, Recurrent Neural Networks (RNN), Adaptive Neuro-Fuzzy Inference System and Higher Order Neural Networks (HONN)
:book: MIT Deep Learning Book in PDF format
Deep Learning By Example, published by Packt
Notes and experiments to understand deep learning concepts
Deep Learning for Beginners, published by Packt
Learn to code deep learning algorithms
Records of deep learning for web attacks detection
Deep Learning Quick Reference, published by Packt
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Getting Started with PyTorch Lightning, Published by Packt
Detection of email phishing attack using CNN
Developed a model to detect Phished emails from legitimate ones using the Spam Assassin dataset. Extracted relevant features by processing the mails using the NLP toolkit. Built various ML models like Naïve Bayes, Random Forest, and Voting Ensemble with the best accuracy of ~72%, and deep learning model like Neural Network with an accuracy of ~96%.
Email Phishing Attempts Detection from the text of email bodies using natural language processing and machine learning
Using machine learning and features extracted from email headers to detect anomalies (i.e., spam, phishing) in email datasets.
Hands-On Artificial Intelligence for Cybersecurity, publised by Packt
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Hands-On Machine Learning for Cybersecurity, published by Packt
Intrusion Detection system for Software Defined Network
A Machine Learning approach for classifying a file as Malicious or Legitimate
Machine Learning for Cybersecurity Cookbook, published by Packt
This Project is based on the ML technology used for Analyzing & detecting the Legitimate files and the Malwarefiles in the system
Malware Detection using Machine Learning
Python program to detect Portable_Executable files as either malicious or legitimate by trying out 5 different classification algorithms and choosing the best one for prediction by comparing their results.
Malware detection project on Android devices using machine learning classification algorithms.
A Machine Learning approach for classifying a file as Malicious or Legitimate
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.