Artificial Intelligence Projects

• Artificial Intelligence Projects
  • Projects
    • CA0 - Introduction to AI
    • CA1 - Search
    • CA2 - Genetics
    • CA3 - Game
    • CA4 - Naive Bayes
    • CA5 - Machine Learning
    • CA6 - Neural Networks
      • Part 1
      • Part 2

Projects

CA0 - Introduction to AI

This project is an introduction to AI and Jupyter Notebooks. We should predict whether a passenger will survive the Titanic disaster.

CA1 - Search

In this projects, the following search algorithms are implemented:

• BFS
• DFS and IDS
• A*
• Weighted A*

CA2 - Genetics

In this project, we implement an equation builder using genetic algorithms.

CA3 - Game

Sim game is implemented in this project using Minimax algorithm. Also, pruning is used to improve the performance of the algorithm.

CA4 - Naive Bayes

This project is an implementation of Naive Bayes algorithm to classify the news into 5 categories.

CA5 - Machine Learning

In this project, we implement the following classifiers to predict whether a person has diabetes or not:

• KNN
• Decision Tree
• Logistic Regression

Random Forest is also implemented as the optimal classifier. GridSearchCV is used to find the best parameters for the classifiers.

CA6 - Neural Networks

This project has two parts:

Part 1

In this part, we implement a neural network from scratch to classify the Arabic letters. The dataset is available here.

Part 2

In this part, wwe use TensorFlow library and Keras API to implement a neural network to classify the CIFAR-10 dataset. The dataset is available here.