Deep Learning – Intelligent Additive Manufacturing

1. Introduction

1.1 Introduction

2. Optimization

2.1 Optimization introduction

2.2 Exponentially Moving Average

2.4 Experiment on Different Optimizers

3. Supervised Learning

3.1 Problem Formation

3.2 Cross-Validation

3.3 Overfitting & Underfitting

4. Regularization

4.2 L1/L2 Norm Regularization

4.4 Early Stopping

4.5 Data Augmentation

4.6 Experiment on Regularization

5. Normalization

5.1 Dataset Normalization

5.2 Normalization Layers

6. Initialization

6.1 Motivation

6.2 Effect on training Dynamics

6.3 Common initialization schemes

6.4 Initializing parameters in Pytorch

7. Hyperparameters Searching

7.1 Motivation

7.2 Methods

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