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Creating a Webpage - A Beginner's Guide (HTML, CSS, JavaScript)

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Creating a Webpage - A Beginner's Guide (HTML, CSS, JavaScript) By Naomi A. Prerequisites: Before diving in, make sure you have access to a reliable text editor or integrated development environment (IDE) to create your HTML code. I personally recommend Visual Studio Code, an incredibly versatile tool that supports multiple programming languages. It's an excellent choice, especially for web development projects. Introduction: Welcome to this beginner-friendly demonstration of creating a simple web page using HTML, CSS, and JavaScript. In just 70 lines of code (with most of it dedicated to styling), you'll witness the possibilities that can be achieved! Please note that this is not an in-depth tutorial for HTML, CSS, or JavaScript. However, it serves as a great starting point for those who are curious about the potential of these languages. Here's a summary of what is covered here: The code starts with a document type declaration ( <!DOCTYPE html> ) specifying that
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Teaching Computers to Play Tic Tac Toe: A Reinforcement Learning Approach

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Teaching Computers to Play Tic Tac Toe: A Reinforcement Learning Approach by Naomi A.  You can see the full code on GitHub: https://github.com/SQLNoggin/Smart-TicTacToe-RL_NaomiA.git This Python script implements a reinforcement learning agent to play the game of Tic Tac Toe. The agent is trained through Q-learning, a type of model-free reinforcement learning that uses a Q-table to estimate the value of taking specific actions in particular states. Let's break down the key aspects:   Overview The script uses the Tkinter library to create a graphical user interface (GUI) where the Tic Tac Toe game can be played. NumPy is used for numerical operations, and the pickle library is used to save and load the Q-table to/from a file. Constant and Hyperparameter Definitions PLAYER_X and PLAYER_O : Constants representing the two players (1 for X and -1 for O). EMPTY : Constant representing an empty cell on the Tic Tac Toe board. ALPHA : The learning rate used in the Q-learning updates. GAMMA
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