Welcome to my collection of projects completed as part of Harvard's CS50’s Introduction to Artificial Intelligence with Python course. This repository contains 12 projects demonstrating a variety of AI and machine learning concepts, from search algorithms and knowledge representation to neural networks and natural language processing.
I earned my certification in AI with Python through both Harvard and edX:
You can view my course progress and grades in the official CS50 AI Gradebook.
All 12 completed projects can be found in this repository:
The following are the 12 projects I completed during the course:
- Degrees of Separation – Finding the shortest path between actors using breadth-first search.
- Tic-Tac-Toe – Implementing an AI that plays optimally using the Minimax algorithm.
- Knight's Logic Puzzle – Encoding logic puzzles as knowledgebases and using propositional logic to infer solutions.
- Minesweeper – Creating an intelligent Minesweeper player using probability and logical inference.
- PageRank – Simulating the PageRank algorithm used by search engines.
- Heredity – Using Bayesian networks to model gene inheritance.
- Crossword – Solving crossword puzzles using backtracking and arc-consistency.
- Shopping – Predicting whether online shoppers will complete a purchase using machine learning techniques.
- Nim – Building a reinforcement learning agent that plays the game of Nim.
- Traffic – Using convolutional neural networks to identify German traffic signs.
- Parser – Building a probabilistic context-free grammar (PCFG) parser for natural language.
- Attention – Building an AI to predict a masked word in a text sequence.
Each project contains its own directory with the necessary Python files and any data used. To run any project, follow these steps:
Important
Some projects also require downloading additional assets from external sources, like the gtsrb dataset for the Traffic project. Refer to the relavant project link above and download the appropriate assets noted in the project description.
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Clone the repository:
git clone https://github.com/becks256/cs50.git cd cs50 -
Navigate to the project you want to explore:
cd project-directory -
Install the required dependencies:
pip install -r requirements.txt
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Run the project using Python:
python project_file.py
- Python: All projects are implemented in Python.
- Libraries: Various projects make use of libraries such as
NumPy,TensorFlow,OpenCV,scikit-learn,nltk, andHuggingFacedepending on the requirements.
- This repository is for educational purposes only. Feel free to fork or clone the repository for your own learning, but kindly do not submit these solutions to the course or claim them as your own work.
- Harvard University and CS50 for providing this excellent course on AI.
- edX for hosting the course platform.