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Cross-Entropy Loss: Detailed Explanation and Derivation (D2P)1. What is Cross-Entropy Loss?Cross-entropy loss is a commonly used loss function in classification tasks. It measures the dissimilarity between the true labels $y$ and the predicted probabilities $\hat{y}$ output by the model. The goal is to minimize the cross-entropy loss to ensure the predicted probabilities match the true labels as..

7 Neural Network Optimization Methods1. Neural Architecture Search (NAS)NAS automates the design of neural network architectures by searching for optimal configurations of layers, connections, and operations. This method removes the need for manual architecture tuning and is widely used in tasks where efficiency and accuracy trade-offs matter.Year: 2017Common Applications: Image classification (..

Universal Approximation TheoremTheoremLet $f: \mathbb{R}^n \to \mathbb{R}$ be a continuous function defined on a compact domain $D \subseteq \mathbb{R}^n$. For any $\epsilon > 0$, there exists a feedforward neural network with a single hidden layer, using a nonlinear, continuous activation function $\phi: \mathbb{R} \to \mathbb{R}$, such that:$$\sup_{x \in D} |f(x) - \hat{f}(x)| $$where $\hat{f}..

1. https://docs.anaconda.com/miniconda/#miniconda-latest-installer-links 접속하여, installer download 하기2. 시작화면에서 miniconda 실행하기3. miniconda 콘솔에서, jupyter notebook 설치 및 실행하기하위 command 한줄씩 실행conda initconda create --name nn python=3.9 -ypip install torch==2.0.0 torchvision==0.15.1pip install d2lcd c:/mkdir nnconda activate nnjupyter notebook4. 새로운 notebook 파일 생성하기