🤖 Neural Network Labs

---

📝 Table of Contents

• 📙 Overview
• ✨ Contributors
• 🔒 License

---

📙 Overview

• My solutions to practice labs in Neural Network labs in Computer engineer department at Cairo University


• The Content
  • Python Review (Link)
  • Operators
  • DataTypes
  • Containers
  • Flow Control Statements
  • Functions
  • Numpy
  • Pandas
  • MatPlot Lib
  • Density Estimation Techniques (Link)
  • Classification of multivariate data
  • The Bayes classification rule
  • Bayesian Classifier (Link)
  • Implement and assess the performance of the Bayesian Classifier
  • Machine Learning Terminlology
  • Density Estimation (Link)
  • Implement one of the density estimation methods
  • Choose a suitable bump function (Parzen window)
  • Principal Component Analysis (Link)
  • Implementing PCA
  • Dimensionality Reduction with PCA
  • Projecting the data onto the principal components
  • Reconstructing an approximation of the data
  • Visualizing the projections
  • AdaBoost Classifier (Link)
  • Classifiers Boosting Algorithms
  • Implementing Adaboost_classifier

---

👑 Contributors

Eslam Ashraf

---

🔒 License

Note: This software is licensed under MIT License, See License for more information ©EslamAsHhraf.