Model Training and Optimization
6 resources created by 4 users
Model Training and Optimization
- All Machine Learning resources
- Types of Learning26
- Machine Learning Workflow and Deployment13
- Data Preparation7
- Feature Engineering and Dimensionality Reduction12
- Model Evaluation and Generalization14
- Regression25
- Classification8
- Decision Trees and Ensemble Learning11
- Support Vector Machines and Kernel Methods5
- Bayesian and Probabilistic Models13
- Clustering18
- Neural Networks and Deep Learning5
- Association Rules and Recommender Systems5
- Machine Learning Applications10
Top Model Training and Optimization resources
Flashcards
Notes
-
week10 stochastic gradient descent : for dealing with large datasets - where batch gradient descent will be slower; because batch uses all 'm' examples in each iteration; randomly shuffle dataset then use below algorithm : u...
-
Hyper paramter What is the Difference Between a Parameter and a Hyperparameter? What is the Model Parameter? A model parameter is a configuration variable that is internal to the model and whose value can be estimated from data. The...
-
gradient descent :why is gradient descent needed? to find the minimum of a function...as in the cost function J(theta0, theta1) how does it work? start with theta0 and theta1 compute J(theta0, theta1) modify theta0 , theta1 to ...
-
Cost Function
More Machine Learning topics
All of Machine LearningTypes of LearningMachine Learning Workflow and DeploymentData PreparationFeature Engineering and Dimensionality ReductionModel Evaluation and GeneralizationRegressionClassificationDecision Trees and Ensemble LearningSupport Vector Machines and Kernel MethodsBayesian and Probabilistic ModelsClusteringNeural Networks and Deep LearningAssociation Rules and Recommender SystemsMachine Learning Applications