This project is an introduction to AI and Jupyter Notebooks. We should predict whether a passenger will survive the Titanic disaster.
In this projects, the following search algorithms are implemented:
- BFS
- DFS and IDS
- A*
- Weighted A*
In this project, we implement an equation builder using genetic algorithms.
Sim
game is implemented in this project using Minimax algorithm. Also, pruning is used to improve the performance of the algorithm.
This project is an implementation of Naive Bayes algorithm to classify the news into 5 categories.
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.
This project has two parts:
In this part, we implement a neural network from scratch to classify the Arabic letters. The dataset is available here.
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.