Using the Titanic passengers dataset, prediction of whether a passenger will survive or not is done. Also some of the Python data science libraries such as pandas, NumPy, and matplotlib in Jupyter Notebook was used.
A problem is solved using the following search algorithms:
- BFS
- DFS & IDS
- A* & Weighrted A*
An equation builder is implemented using the genetic algorithms. The problem gives an equation of length n and its answer, genetic methods are used to find what combination of operands and operators satisfy the equation.
In this project the Sim game is implemented using Minimax algorithm. One of the players uses the alpha-beta minimax algorithm, while the other agent plays randomly.
Classification of news in 5 categories is done using the Naive Bayes algorithm.
Prediction of wheter a person has diabetes or not is implemented using the following classifiers:
- Decision Tree
- K-Nearest Neighbors
- Logistic Regression
- Random Forest
This project has two phases:
- Phase 1: A neural network is implemented and trained to classify images of Arabic handwritten characters.
- Phase 2: Tensorflow library and Keras API are used to classify the CIFAR-10 dataset.