User contributions for Mr. Goldstein
Results for Mr. Goldstein talk block log uploads logs
A user with 480 edits. Account created on 5 July 2025.
8 July 2025
- 18:1818:18, 8 July 2025 diff hist −37 10.3.3 Support Vector Machines (SVM) No edit summary current Tag: Visual edit
- 18:1418:14, 8 July 2025 diff hist +1,947 N 10.3.3 Support Vector Machines (SVM) Created page with "=== 10.3.3 Support Vector Machines (SVM) === Imagine you have a bunch of red dots and blue dots scattered on a piece of paper, and you want to draw a straight line that best separates the red dots from the blue dots. '''Support Vector Machines (SVM)''' try to find the "best" line (or a more complex boundary in higher dimensions) that not only separates the groups but also maximizes the margin (the distance) between the line and the closest data points from each group. *..." Tag: Visual edit
- 17:5817:58, 8 July 2025 diff hist +111 Main Page No edit summary Tag: Visual edit
- 17:5717:57, 8 July 2025 diff hist +11 10.3.2 Decision Trees, Random Forests No edit summary current Tag: Visual edit
- 17:5017:50, 8 July 2025 diff hist +3,403 N 10.3.2 Decision Trees, Random Forests Created page with "=== 10.3.2 Decision Trees, Random Forests === These algorithms are powerful and intuitive, often used for both classification and regression tasks. They mimic human-like decision-making processes. ==== Decision Trees ==== Imagine you're trying to decide what to wear based on the weather. You might follow a mental flowchart: "Is it raining? If yes, wear a raincoat. If no, is it cold? If yes, wear a jacket. If no, wear a t-shirt." A '''Decision Tree''' works exactly like..." Tag: Visual edit
- 17:3317:33, 8 July 2025 diff hist +50 Main Page No edit summary Tag: Visual edit
- 17:3317:33, 8 July 2025 diff hist +3,295 N 10.3.1 Linear Regression, Logistic Regression Created page with "=== 10.3.1 Linear Regression, Logistic Regression === These two algorithms are fundamental in supervised learning and are often among the first ones learned when studying machine learning. They are used for prediction tasks. ==== Linear Regression ==== Imagine you have a scatter plot of data points showing how much ice cream is sold at different temperatures. As the temperature goes up, ice cream sales generally go up too. '''Linear Regression''' is like drawing the "be..." current Tag: Visual edit
- 17:2417:24, 8 July 2025 diff hist +30 Main Page No edit summary Tag: Visual edit
- 17:2217:22, 8 July 2025 diff hist +481 N 10.3 Common ML Algorithms Created page with "=== 10.3 Common ML Algorithms === Now that we understand the different types of Machine Learning (Supervised, Unsupervised, Reinforcement), let's dive into some of the most common and fundamental algorithms used to make machines learn. These algorithms are the "recipes" that computers follow to find patterns, make predictions, or group data. We'll focus on algorithms that fall under Supervised and Unsupervised Learning, as they are widely used in many real-world applica..." current Tag: Visual edit
- 16:3916:39, 8 July 2025 diff hist +55 Main Page No edit summary Tag: Visual edit
- 16:3816:38, 8 July 2025 diff hist +4,101 N 10.5.2.1 Generative Pre-trained Transformers (GPT) Created page with "==== 10.5.2.1 Generative Pre-trained Transformers (GPT) ==== The "GPT" in models like ChatGPT stands for '''Generative Pre-trained Transformer'''. This name precisely describes the core architecture and training methodology that makes these powerful language models work. Let's break down each part of the acronym: * '''Generative:''' ** '''What it means:''' This refers to the model's ability to '''create new content''' (specifically, text) that is original and coherent,..." current Tag: Visual edit
- 16:2916:29, 8 July 2025 diff hist +2 Main Page No edit summary Tag: Visual edit
- 16:2816:28, 8 July 2025 diff hist +56 Main Page No edit summary Tag: Visual edit
- 16:1316:13, 8 July 2025 diff hist +111 Main Page No edit summary Tag: Visual edit
- 16:0316:03, 8 July 2025 diff hist −17 10.5.2 Large Language Models (LLMs) No edit summary current Tag: Visual edit
- 16:0116:01, 8 July 2025 diff hist +2,820 N 10.5.2 Large Language Models (LLMs) Created page with "=== 10.5.2 Large Language Models (LLMs) === Imagine a super-smart robot that has read almost every book, article, and piece of text ever written on the internet. It knows how words fit together, how sentences are formed, and even facts about the world. This robot can then use all that knowledge to create new text, answer questions, or even write stories! That's a bit like what a '''Large Language Model (LLM)''' is. LLMs are a special and very powerful type of Artificial..." Tag: Visual edit
- 15:4715:47, 8 July 2025 diff hist +40 Main Page No edit summary Tag: Visual edit
- 15:4615:46, 8 July 2025 diff hist +3,541 N 10.5.1 Basic tasks and applications Created page with "=== 10.5.1 Basic tasks and applications === Both NLP and Computer Vision are used in many ways every day. Here are some basic tasks and applications for each: '''Natural Language Processing (NLP) Tasks & Applications:''' # '''Text Translation:''' #* '''Task:''' Converting text from one human language to another. #* '''Application:''' Google Translate, which lets you translate websites, documents, or spoken words instantly. # '''Sentiment Analysis:''' #* '''Task:''' Fig..." current Tag: Visual edit
- 15:4015:40, 8 July 2025 diff hist +66 Main Page No edit summary Tag: Visual edit
- 15:3915:39, 8 July 2025 diff hist +944 N 10.5 Natural Language Processing (NLP) / Computer Vision (CV) Created page with "=== 10.5 Natural Language Processing (NLP) / Computer Vision (CV) === Imagine a computer that can understand what you're saying, or "see" what's in a picture. That's what '''Natural Language Processing (NLP)''' and '''Computer Vision (CV)''' are all about! These are two huge and exciting areas within Artificial Intelligence where computers try to understand and work with human-like information. * '''Natural Language Processing (NLP):''' This is about teaching computers..." current Tag: Visual edit
- 15:2915:29, 8 July 2025 diff hist +7 Main Page No edit summary Tag: Visual edit
- 15:2815:28, 8 July 2025 diff hist +34 Main Page No edit summary Tag: Visual edit
- 15:2715:27, 8 July 2025 diff hist +2,905 N 10.2.3 Reinforcement Learning Created page with "==== 10.2.3 Reinforcement Learning ==== Imagine you're training a dog to do tricks. You don't tell the dog ''exactly'' how to sit; instead, you give it a treat (a reward) when it gets closer to sitting, and you don't give a treat (a punishment, or lack of reward) when it does something wrong. Over time, the dog figures out the right actions to get the treats. '''Reinforcement Learning (RL)''' is a type of Machine Learning where an "agent" (the computer program) learns t..." current Tag: Visual edit
- 15:2215:22, 8 July 2025 diff hist +72 Main Page No edit summary Tag: Visual edit
- 15:2215:22, 8 July 2025 diff hist +2,847 N 10.2.2 Unsupervised Learning (Clustering, Dimensionality Reduction) Created page with "==== 10.2.2 Unsupervised Learning (Clustering, Dimensionality Reduction) ==== Imagine you have a big box full of mixed LEGO bricks of different colors and shapes, but no one tells you what to do with them. You start playing around and notice that certain colors tend to go together, or certain shapes fit nicely with others. You start sorting them into groups based on what you observe, without any instructions. '''Unsupervised Learning''' is a type of Machine Learning whe..." current Tag: Visual edit
- 15:1315:13, 8 July 2025 diff hist +60 Main Page No edit summary Tag: Visual edit
- 15:1215:12, 8 July 2025 diff hist +2,510 N 10.2.1 Supervised Learning (Regression, Classification) Created page with "==== 10.2.1 Supervised Learning (Regression, Classification) ==== Imagine you're learning to identify different types of fruits. Someone shows you many pictures, and for each picture, they tell you: "This is an apple," "This is a banana," "This is an orange." After seeing many examples with the correct labels, you learn to identify new fruits on your own. '''Supervised Learning''' is the most common type of Machine Learning. It's like having a teacher (the "supervisor")..." current Tag: Visual edit
- 14:5914:59, 8 July 2025 diff hist +35 Main Page No edit summary Tag: Visual edit
- 14:5514:55, 8 July 2025 diff hist +35 Main Page No edit summary Tag: Visual edit
- 14:5414:54, 8 July 2025 diff hist +604 N 10.2 Types of Machine Learning Created page with "=== 10.2 Types of Machine Learning === Machine Learning (ML) is a huge and exciting part of AI. It's how computers learn to do things without being specifically told every single step. Instead, they learn from examples, just like you learn from experience. There are three main ways machines learn: # '''Supervised Learning:''' Learning from examples where we know the right answers. # '''Unsupervised Learning:''' Finding patterns in data without knowing the right answers..." current Tag: Visual edit
- 14:4314:43, 8 July 2025 diff hist +103 Main Page No edit summary Tag: Visual edit
- 14:3914:39, 8 July 2025 diff hist +24 Main Page No edit summary Tag: Visual edit
- 14:3814:38, 8 July 2025 diff hist +30 Main Page No edit summary Tag: Visual edit
- 14:3714:37, 8 July 2025 diff hist +3,038 N 10.1.2 Applications of AI Created page with "==== 10.1.2 Applications of AI ==== AI is no longer just science fiction; it's everywhere around us! It's used in countless ways to make our lives easier, safer, and more fun. Here are just a few examples of how AI is being used today: # '''Voice Assistants:''' #* '''What it does:''' Understands your spoken words and responds to your commands. #* '''Examples:''' Siri, Google Assistant, Amazon Alexa. You can ask them questions, set alarms, play music, or control smart h..." current Tag: Visual edit
- 14:3114:31, 8 July 2025 diff hist +48 Main Page No edit summary Tag: Visual edit
- 14:2914:29, 8 July 2025 diff hist +2,703 N 10.1 Introduction to AI Created page with "=== '''10.1 Introduction to AI''' === When we talk about Artificial Intelligence, it's helpful to understand that there are different levels of "smartness" we're trying to achieve in machines. ==== '''10.1.1 Strong AI vs. Weak AI''' ==== When scientists and engineers talk about AI, they often divide it into two main types: * Weak AI (or Narrow AI): ** What it is: This is the kind of AI we have today and use every day. Weak AI is designed and trained for a very specifi..." current Tag: Visual edit
- 14:2214:22, 8 July 2025 diff hist +53 Main Page No edit summary Tag: Visual edit
- 14:2214:22, 8 July 2025 diff hist +4 Main Page No edit summary Tag: Visual edit
- 14:2114:21, 8 July 2025 diff hist +1,239 N 10.0 Artificial Intelligence (AI) & Machine Learning Created page with "= 10.0 Artificial Intelligence (AI) & Machine Learning = Imagine a future where robots can talk to you like a human, cars can drive themselves, and computers can understand your voice commands. This amazing future is being built with '''Artificial Intelligence (AI)''' and '''Machine Learning (ML)'''! '''Artificial Intelligence (AI)''' is a big field in computer science that focuses on making machines "smart." It's about creating computer systems that can do things that..." current Tag: Visual edit
- 14:1514:15, 8 July 2025 diff hist +65 Main Page →4.0 Data Structures Algorithms (DSA) Tag: Visual edit
- 13:3413:34, 8 July 2025 diff hist +792 N 4.1 Data Structures Created page with "=== 4.1 Data Structures === As we just learned, a '''Data Structure''' is a specific way of organizing data in a computer's memory. It's not just about putting data in a list; it's about arranging it in a way that makes certain operations (like adding new data, finding data, or deleting data) very fast and efficient. Think of it as choosing the best container for your items: * If you have a stack of plates, you always add to the top and take from the top. * If you have..." current Tag: Visual edit
- 13:3113:31, 8 July 2025 diff hist +1,241 N 4.0 Data Structures Algorithms (DSA) Created page with "= 4.0 Data Structures & Algorithms (DSA) = Imagine you have a huge library with millions of books. If they were all just dumped in a giant pile, finding a specific book would be impossible! But if they're organized on shelves, by genre, by author, and with a catalog system, finding any book becomes much easier. In Computer Science, '''Data Structures''' are like the different ways you can organize and store information (data) in a computer's memory. They are special for..." current Tag: Visual edit
- 13:1713:17, 8 July 2025 diff hist +41 Main Page →3.6 Error Handling & Debugging Tag: Visual edit
- 13:1713:17, 8 July 2025 diff hist +3,558 N 3.6.3 Debugging Techniques and Tools Created page with "=== 3.6.3 Debugging Techniques and Tools === Imagine you've built your LEGO castle, but one tower keeps falling over. You know there's a problem, but you don't know exactly ''why'' or ''where''! You need to become a detective. '''Debugging''' is the process of finding and fixing errors (bugs) in your computer program. It's a skill every programmer develops, and it often takes more time than writing the code itself! Here are some common techniques and tools used for deb..." current Tag: Visual edit
- 13:0613:06, 8 July 2025 diff hist +41 Main Page →3.6 Error Handling & Debugging Tag: Visual edit
- 13:0513:05, 8 July 2025 diff hist +3,142 N 3.6.2 Exception Handling (try-catch) Created page with "=== 3.6.2 Exception Handling (try-catch) === Imagine you're a robot trying to open a file on a computer. What if the file isn't there? Instead of just stopping and saying "Error!", you want the robot to be polite and say, "I couldn't find the file, would you like me to try again?" '''Exception Handling''' is a programming technique that allows your program to '''gracefully deal with runtime errors''' (also called "exceptions"). Instead of crashing when something unexpec..." current Tag: Visual edit
- 13:0113:01, 8 July 2025 diff hist +51 Main Page →3.6 Error Handling & Debugging Tag: Visual edit
- 13:0013:00, 8 July 2025 diff hist +3,632 N 3.6.1 Types of Errors (Syntax, Runtime, Logic) Created page with "=== 3.6.1 Types of Errors (Syntax, Runtime, Logic) === When a program doesn't work right, it's usually because of one of three main types of errors: * '''Syntax Errors:''' ** '''What they are:''' These are like grammar mistakes or spelling errors in your programming language. Just like you'd get a red line under a misspelled word in a word processor, the computer's language checker (called a '''compiler''' or '''interpreter''') will catch these errors ''before'' your pr..." current Tag: Visual edit
- 12:5512:55, 8 July 2025 diff hist +4 Main Page →3.6 Error Handling & Debugging Tag: Visual edit
- 12:5412:54, 8 July 2025 diff hist +714 N Error Handling & Debugging Created page with "=== 3.6 Error Handling & Debugging === Imagine you're building a complex LEGO castle, and suddenly a piece breaks, or you put a piece in the wrong spot. The castle won't look right, or it might even fall apart! In programming, just like building, things can go wrong. '''Errors''' are problems that stop your program from working correctly. '''Error Handling''' is about planning for these problems and making your program deal with them gracefully, instead of just crashing..." current Tag: Visual edit