딥러닝 목차 한눈에 보기

• 전처리 : 데이터 정규화(Standard Scaler, Robust Scaler, min-max Scaler, Normalizer), 학습/검증 데이터 분류(data split), Batch 구성설정, 인코딩(Word2Vec 등)
• Layers : Flatten, Dense(Fully Connected), Activation(sigmoid, ReLU, Softmax,tanh), BatchNorm, DropOut, Convolution, Pooling
• 가중치 초기화 : Random(Default), Xavier (GlorotNormal), He(HeNormal)
• 가중치 학습 : SGD, Adam, AdamW, Momentum, LearningRate, Weight Decay, Weight Constraint
• 학습관련 : Epoch, Iteration, EarlyStop, LearningRateDecay, BatchSize

참고자료

• https://taeu.github.io/cs231n/deeplearning-cs231n-Neural-Networks-2/