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Chapter 3
Lesson 71: Model Initialization – Explaining the Impact of Parameter Initial Values on Learning
Recap of the Previous Lesson and Today's Theme In the previous lesson, we learned about optimizers in machine learning models. I hope you gained an understanding of techniques like Adam, RMSprop, and Adagrad, which efficiently optimize m... -
Chapter 3
Lesson 70: Types of Optimizers
What is an Optimizer? Hello! In this lesson, we’ll discuss optimizers, a key element in neural network training. Optimizers are essential for ensuring that models minimize errors efficiently and make accurate predictions. Specifically, o... -
Chapter 3
Lesson 69: Dropout — A Regularization Technique to Prevent Overfitting
What is Dropout? Hello! Today, we’ll learn about Dropout, a powerful regularization technique used to prevent overfitting in neural networks. Deep learning models, as they learn from data, often face a challenge known as overfitting, whe... -
Chapter 3
Lesson 68: Batch Normalization
What is Batch Normalization? Hello! In this episode, we'll explore "Batch Normalization," an essential technique for stabilizing deep learning training and improving model accuracy. Batch normalization is widely used to prevent vanishing... -
Chapter 3
Lesson 67: The Exploding Gradient Problem
What is the Exploding Gradient Problem? Hello! In this lesson, we’ll be discussing the exploding gradient problem, a key issue in the training of neural networks. Similar to the vanishing gradient problem we covered previously, the explo... -
Chapter 3
Lesson 66: The Vanishing Gradient Problem
What is the Vanishing Gradient Problem? Hello! Today's topic covers a common challenge in deep learning known as the Vanishing Gradient Problem. This issue arises particularly in deep neural networks and can severely hinder the learning ... -
PROMPT
Expressing Construction Machinery with Prompts: Mastering Image Generation AI
How to Depict Construction Machinery with Generative AI Basics of Generative AI and Prompts When using generative AI to express construction machinery at work on a construction site, the level of detail in your prompts greatly influences... -
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Expressing Snowy Landscapes with Prompts: Utilizing Generative AI like MidJourney and FLUX.1
How to Depict Snowy Landscapes with Generative AI Basics of Prompts to Bring Out the Harsh Natural Environment of Snow Countries To realistically express snowy landscapes using image generation AI like MidJourney or FLUX.1, it is importa... -
PROMPT
Expressing Forest Landscapes with Prompts: How to Use AI for Image Generation
How to Represent Forest Landscapes with AI Basics of AI and Prompts When using AI to generate forest or jungle landscapes, the level of detail included in the prompt significantly impacts the result. Specifying the type of forest (conife... -
PROMPT
Expressing Tropical Landscapes with Prompts: How to Use MidJourney, Stable Diffusion, and Other AI Tools
How to Represent Tropical Landscapes with AI Basics of Prompts to Bring Out the Tropical Atmosphere To realistically express tropical landscapes using image generation AIs like MidJourney, Stable Diffusion, or FLUX.1, it’s essential to i... -
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Expressing Snowy Mountain Landscapes with Prompts: How to Use MidJourney, and Other AI Tools
How to Depict Snowy Mountains with Generative AI Basics of Generative AI and Prompts When expressing snowy mountain landscapes with generative AI, the details in your prompts significantly impact the results. To portray snow-covered moun... -
Chapter 3
Lesson 65: Types of Activation Functions
What is an Activation Function? Hello! In the previous lesson, we covered backpropagation, a key process in training neural networks. This time, we’ll focus on activation functions, which play a crucial role in neural networks. Activatio... -
Chapter 3
Lesson 64: Backpropagation — Learning by Propagating Errors Backward
Recap and Today's Topic Hello! In the previous session, we explored forward propagation, which explains how input data flows through the layers of a neural network to generate predictions. Today, we’ll dive into the reverse process: back... -
Chapter 3
Lesson 63: Forward Propagation
What is Forward Propagation? Hello! In the previous lesson, we learned about Multilayer Perceptrons (MLP) and gained an understanding of the basic structure of neural networks. In this lesson, we will dive into a crucial process called f... -
Chapter 3
Lesson 62: Multi-Layer Perceptron (MLP) — Understanding a Basic Deep Learning Model
Recap and Today's Topic Hello! In the previous session, we discussed the fundamental concepts of Deep Learning, which uses neural networks to automatically extract features from data by stacking multiple layers. Today, we will delve into...
