Projects for my Udacity Artificial Intelligence Nanodegree

In this lesson, you'll get taste of the power of Artificial Intelligence by developing an algorithm to solve every Sudoku puzzle. We won't go particularly in depth into the techniques yet, which we'll do in future lessons. For now, enjoy the fun of building your first AI agent and get coding!

In this lesson, you'll build a Game-Playing agent that defeats opponents in Isolation. Along the way, you'll learn about advanced Game-Playing techniques such as Iterative Deepening, Alpha-Beta Pruning, and Expectimax.

In this optional exercise you can check your understanding of simulated annealing by implementing the algorithm in a Jupyter notebook and using it to solve the Traveling Salesman Problem (TSP) between US state capitals. Additonally, this project is implemented in Scala.

Explore how we can use logic and search to plan out complex itineraries. Many of these planning approaches are the same ones used to power Self-Driving Cars!

Learn to process sequences and time-series data using Hidden Markov Models.

Predict sentiment (positive/negative) of IMBD reviews with Keras.

Welcome to the Convolutional Neural Networks (CNN) project! In this project, you will learn how to build a pipeline to process real-world, user-supplied images. Given an image of a dog, your algorithm will identify an estimate of the canine’s breed. If supplied an image of a human, the code will identify the resembling dog breed.

Along with exploring state-of-the-art CNN models for classification, you will make important design decisions about the user experience for your app. Our goal is that by completing this lab, you understand the challenges involved in piecing together a series of models designed to perform various tasks in a data processing pipeline. Each model has its strengths and weaknesses, and engineering a real-world application often involves solving many problems without a perfect answer. Your imperfect solution will nonetheless create a fun user experience!