Mastering ML:Hyperparameter Optimization & Feature Selection
git.ir
Mastering ML:Hyperparameter Optimization & Feature Selection
This course covers fundamentals of machine learning through practical application with libraries such as scikit-learn, scikit-optimize, Keras, Optuna, and TensorFlow. You'll discover how to effectively construct, adjust, and optimize models, ranging from simple models to sophisticated neural nets. Regardless of experience level, this course ...
177 viewsApr 28, 2024
Hyperparameter Tuning
What Is Hyperparameter Tuning? | IBM
What Is Hyperparameter Tuning? | IBM
ibm.com
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Automatic Hyperparameter Tuning - A Visual Guide (Part 1) | Antonin Raffin | Homepage
Automatic Hyperparameter Tuning - A Visual Guide (Part 1) | Antonin Raffin | Homepage
github.io
May 15, 2023
Hyperparameter tuning is a crucial process in machine learning that involves selecting the optimal set of hyperparameters for a model to improve its performance. Unlike model parameters, which are learned during training, hyperparameters are predefined values that influence the training process itself, such as learning rate, batch size, and number of layers in a neural network. The goal of hyperparameter tuning is to find the best combination that maximizes the model's accuracy or minimizes erro
0:57
Hyperparameter tuning is a crucial process in machine learning that involves selecting the optimal set of hyperparameters for a model to improve its performance. Unlike model parameters, which are learned during training, hyperparameters are predefined values that influence the training process itself, such as learning rate, batch size, and number of layers in a neural network. The goal of hyperparameter tuning is to find the best combination that maximizes the model's accuracy or minimizes erro
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