Studying Repository

Deep learning Studying(58) - Deep Classification 직접 해보기

Part.7 Deep Classification 실습

Deep learning Studying(57) - Confusion Matrix

Part.6 Confusion Matrix

Deep learning Studying(56) - Softmax & Cross Entropy

Part.5 Softmax & Cross Entropy

Deep learning Studying(55) - 분류 (Classification)

Part.4 Classification

Deep learning Studying(54) - Deep Binary Classification 실습

Part.3 Binary Classification 실습

Deep learning Studying(53) - Precision & Recall

Part.2 Evaluation Metrics

Deep learning Studying(52) - Deep Binary Classification

Part.1 Deep Binary Classification

Deep learning Studying(51) - Split into Train/Valid/Test set

Part.3 실습 실험 환경 구성하기

Deep learning Studying(50) - 오버피팅이란?

Part.2 오버피팅이란?

Deep learning Studying(49) - Working Process

Part.1 실험 과정 소개

Deep learning Studying(48) - Wrap-up

Part.6 Wrap-up

Deep learning Studying(47) - 실습 Adam Optimizer 적용하기

Part.5 실습 Adam Optimizer 적용하기

Deep learning Studying(46) - Adaptive LR Optimizer

Part.4 Adaptive LR Optimizer 수식

Deep learning Studying(45) - Momentum & Adaptive LR

Part.3 Momentum & Adaptive LR

Deep learning 강좌(44) - 효율적인 연구 진행 방법

Part.2 Hyper-Parameter 별 결과물 관리

Deep learning Studying(43) - Hyper Parameters

Part.1 Hyper-Parameters

Deep learning Studying(42) - SGD 적용하기

Part.4 실습 SGD 적용하기

Deep learning Studying(41) - Batch Size에 따른 특성

Part.3 Batch Size에 따른 특성

Deep learning Studying(40) - Intuiton SGD

Part.2 Intuiton SGD

Deep learning Studying(39) - Stochastic Gradient Descent

Part.1 Stochastic Gradient Descent (SGD)

Deep learning Studying(38) - ReLU

Part.5 ReLU

Deep learning Studying(37) - Gradient Vanishing

Part.4 Gradient Vanishing

Deep learning Studying(36) - 수식 Back propagation

Part.3 수식 Back propagation

Deep learning Studying(35) - Back propagation

Part.2 Back propagation

Deep learning Studying(34) - Deep Neural Networks

Part.1 Deep Neural Networks

Deep learning Studying(33) - Logistic Regression Warm-up

Part.7 Warm-up

Deep learning Studying(32) - Logistic Regression 실습

Part.6 Logistic Regression 실습

Deep learning Studying(31) - 수식 Logistic Regression

Part.5 수식 Logistic Regression

Deep learning Studying(30) - Binary Cross Entropy

Part.4 Loss Function - Binary Cross Entropy

Deep learning Studying(29) - Logistic Regression

Part.3 Logistic Regression

Deep learning Studying(29) - Sigmoid Function 실습

Part.2 Sigmoid Function 실습

Deep learning Studying(28) - Activation Function Sigmoid

Part.1 활성함수 Function Sigmoid

Deep learning Studying(27) - Linear Regression 실습

Part.3 Linear Regression 실습

Deep learning Studying(26) - 수식 Linear Regression

Part.2 수식 Linear Regression

Deep learning Studying(25) - Linear Regression by Gradient Descent

Part.1 Linear Regression by Gradient Descent

Deep learning Studying(24) - PyTorch Autogrid 소개

Part.6 PyTorch Autogrid 소개.

Deep learning Studying(23) - PyTorch AutoGrad

Part.5 Gradient Descent 구현

Deep learning Studying (22) - Learning Rate in Gradient Descent

Part.4 Learning rate에 따른 특성

Deep learning Studying(21) - Gradinant Descent

Part.3 Gradinant Descent

Deep learning Studying(20) - Appendix 편미분

Part.2 Appendix 편미분

Deep learning Studying(19) - Appendix 미분

Appendix 미분

Deep learning Studying(18) - Mean Square Error Loss

Part.2 MSE Loss

Deep learning Studying(17) - Loss 함수.

Part.1 Loss Function

Deep learning Studting(15) - GPU 직접 써보기

Part.5 실습 GPU 사용하기

Deep learning Studying(14) - 신경망의 기본 구성 요소

Part.3 Linear Layer

Deep learning Studying(13) - 행렬곱 만들어보기

Part.2 행렬곱 실습

Deep learning Studying(12) - Matrix Multiplication

Part.1 행렬곱

Deep learning Studying(12) - 텐서 자르고 붙이고~

Part.7 Pytorch 실습 유용한 함수들

Deep learning Studying(11) - 텐서 자르고 붙이고~

Part.7 실습 텐서 자르기&붙이기

Deep learning Studying(10) - 텐서 형태 봐꾸어보기

Part.7 실습 텐서 형태 변환

Deep learning Studying(9) - 실습 텐서 기본 연산

Part.5 실습 텐서 기본 연산

Deep learning 실습 텐서 생성하기

Deep learning Studying(7) - What is Tensor?

Part.4 Tensor

Deep learning Syudying (6) - Dataset

Part.3 Dataset

Deep learning Studying(5) - PyTorch 사용법

Part.2 Hello PyTorch!

Deep learning Studying(4) - PyTorch 소개

Part.1 Why PyTorch?

Deep learning Studying(4) - 딥러닝을 위한 기본 수학

Part.4 Appendix. Basic Math

Deep learning Studying(2) - 좋은 인공지능이란?

Part.2 Generalization ~ 3. Workflow

Deep learning Studying(1) - Deep learning 기본 개념

Part.1 딥러닝이란?