AI Plus School - Basics to Applications

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Welcome to our channel dedicated to making Artificial Intelligence accessible to everyone! We offer short, practical AI-related content for anyone interested...

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[14] ChatGPT의 ‘T’, Transformer 전체 구조와 데이터 입력

[14] The ‘T’ in ChatGPT, Transformer Overall Structure and Data Input

LSTM보다 빠르고 가벼운 게이트 순환 유닛 (Gated Recurrent Unit, GRU)

Faster and Lighter than LSTM Gated Recurrent Unit (GRU)

RNN, LSTM 코딩 실습(배추값 예측)

RNN & LSTM coding practice (cabbage price prediction)

시계열 데이터 분석 RNN의 한계를 넘어 장단기 기억 신경망(LSTM)

Beyond the Limitations of RNNs Long Short-Term Memory(LSTM)

시계열 데이터 분석의 핵심 순환 신경망 (RNN)

Time Series Data Analysis Recurrent Neural Networks(RNNs)

이상치 탐지 알고리즘 (Iris 데이터셋 코딩 실습)

Anomaly detection (Hands-on Practice with the Iris Dataset)

이상치 탐지 알고리즘 (Isolation Forest, One-Class SVM)

Anomaly detection (Isolation Forest, One-Class SVM)

이상치 탐지 알고리즘 (Local Outlier Factor)

Anomaly detection (Local Outlier Factor)

(조건부) 변분 오토인코더 (VAE, CVAE)

(Conditional) Variational Autoencoder

오토인코더 실습 (Iris dataset)

Autoencoder(Hands-on practice with iris dataset)

오토인코더(Autoencoder)

Autoencoder (Basic theory)

AI-based hyperspectral imaging for non-destructive rheology prediction of hydrocolloids

합성곱 신경망(CNN) (MNIST 실습)

CNN Hands-on Practice with MNIST

합성곱 신경망(CNN) (기초 이론)

Convolutional Neural Network (Basic theory)

이미지 분류 다층 퍼셉트론(MLP)으로 손글씨 숫자(MNIST) 인식

Image Classification Handwritten Digit Recognition (MNIST) Using Multilayer Perceptron

TensorFlow 실습 다층 퍼셉트론(MLP) 와인 분류