Publications by MSDS 6372: Jacob Turner: Student: Jessica McPhaul link:
quantum study 2
recap of “Quantum Computing Course – Math and Theory for Beginners” video, along with mathematical explanations and Python code examples to illustrate key concepts. Summary: The video provides a comprehensive introduction to quantum computing, covering essential mathematical foundations and core principles. It delves into topics such as c...
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QuartoyQuantum
--- title: "Quantum Study Guide" author: "Jessica McPhaul" date: "2025-02-06" format: html: theme: cosmo code-fold: true html-math-method: katex server: shiny execute: echo: true --- ## Shiny Interactive Component ::: {.cell} ```{.r .cell-code} library(shiny) ::: fluidPage( titlePanel("Old Faithful Geyser Dat...
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Publish Document
--- title: "Quantum Study Guide" author: "Your Name" date: "2025-02-06" format: html server: shiny execute: echo: true --- ## Shiny Interactive Component ::: {.cell} ```{.r .cell-code} library(shiny) ::: fluidPage( titlePanel("Old Faithful Geyser Data"), sidebarLayout( sidebarPanel( sliderInput("bins", ...
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Mod3 Taking it further
3: Logistic Regression Categorical Data Linear to Logistic The Sigmoid Log Loss Minimizing Log Loss Multiclass Context Module Sub Header Demonstration of Logistic Regression Demonstration of Logistic Regression, Part I Demonstration of Logistic Regression, Part II Context Module Sub Header Case Study 2 Case Study 2 Introduction Case Study 2, Part...
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Module 3 Transcript and Guide
Logistic Regression Study Guide Key Concepts 1. Categorical Data Definition: Data based on classes (e.g., red/green/blue, true/false). Transformation: Use one-hot encoding to convert non-numeric data into numeric format. Example: Red = [1, 0, 0], Green = [0, 1, 0], Blue = [0, 0, 1]. Each category is represented by a binary vector. Discrete ...
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QTW Module 3 with quiz
Logistic Regression Study Guide Key Concepts 1. Categorical Data Definition: Data based on classes (e.g., red/green/blue, true/false). Transformation: Use one-hot encoding to convert non-numeric data into numeric format. Example: Red = [1, 0, 0], Green = [0, 1, 0], Blue = [0, 0, 1]. Each category is represented by a binary vector. Discrete ...
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QTW Class 1 into CS1
Class 1 transcript summarized and broken down into sections going into case studfy 1. Course Introduction and Structure Instructor: Professor Slater. Course: “Quantifying the World.” Syllabus and Textbook: Free online textbook available. Key Components of Grading: Case studies (50%): Seven biweekly case studies (odd weeks). Final case ...
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7333QTWModule2
Study Guide: Understanding Overfitting and Regularization in Machine Learning (integrating theory, mathematical foundations, and practical examples to regularization techniques to help understand their impact on overfitting in machine learning. 1. Overfitting Definition: Overfitting occurs when a model is overly tailored to the training data,...
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Dev Drive Setup
Step 1: Setting Up Development Tools on the Dev Drive You’ll need to configure your commonly used tools (like Python, VSCode, WSL, and Docker) to store their files, projects, or data on the Dev Drive. 1. Python (venv or Conda) Using venv: Open a terminal (Command Prompt or PowerShell). Create a Python virtual environment directly on the Dev...
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Jessica McPhaul GIS 7334 Fall 2024 JZ
Week 3 Learn: 3-1 Edinburgh Week 3 pptx 3-2 3-2 These have been on canvas waiting for grades since September 12 Week 4 HACK - This was turned in but you didn’t grade it correctly, overlooking the link as well as the comments. Week 4 Jessica’s Bike Survey Storymap Wheelin’ Around Dallas] Week 5 Week 5 Snow LEARN 7-1 : This was turne...
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