The weights and biases that a model learns during training . For example, in a linear regression model, the parameters consist of the bias (b w 1 w 2
y ′ = b + w 1 x 1 + w 2 x 2 + ⋯ + w n x n In contrast, hyperparameters are the values that you (or a hyperparameter tuning service) supply to the model. For example, learning rate is a hyperparameter.1
목차 목차 관련 글 ML crash course - Linear regression 이 글을 인용: “Define and describe how gradient descent finds the optimal model parameters.” Introduction to Machine Learning 관련 절: Definition of [[Machine learning|ML]] Epoch (machine learning) “The number of epochs is a hyperparameter you set before the model begins training.” 역전파 “A large learning rate will increase or decrease each weight more than a small learning rate.” Machine Learning Systems “Machine Learning Systems provides a systematic framework for understanding and engineering machine learning (ML…” Clipping (machine learning) “Outliers can damage models, sometimes causing weights to overflow during training.” Iteration (machine learning) “A backward pass (backpropagation) to adjust the model's parameters based on the loss and the learning rate.” Self-training (machine learning) “A variant of self-supervised learning that is particularly useful when all of the following conditions are true:” 모델 (기계학습) “In supervised machine learning, a model takes an example as input and infers a prediction as output.” 선형 모델 “(Linear models also incorporate a bias.)” Generalization (machine learning) “Consequently, the model learns the peculiarities of the data in the training set.” Downsampling (machine learning) “For example, before training an image recognition model, downsampling high-resolution images to a lower-resolut…” 지도 학습 “Supervised machine learning is analogous to learning a subject by studying a set of questions and their corresp…” Interpretability (machine learning) “Most linear regression models, for example, are highly interpretable.” 기계학습 “2024-08-24 - What's Really Going On in Machine Learning?” AdaGrad 이 글을 인용: “A sophisticated gradient descent algorithm that rescales the gradients of each parameter, effectively giving ea…” A simple way to prevent neural networks from overfitting 이 글을 인용: “Deep neural nets with a large number of parameters are very powerful machine learning systems.” 분류 모델 “For example, the following are all classification models:” Example (machine learning) “Examples in supervised learning fall into two general categories:” 경사하강법 “Gradient descent is older--much, much older--than machine learning.”