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Artificial Intelligence
Unit 1
Machine Learning
Introduction to Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Model Evaluation and Validation
Unit 2
Deep Learning
Introduction to Deep Learning
Deep Neural Networks
Training Deep Learning Models
Unit 3
Learning to Rank Models (LLM)
Introduction to Learning to Rank Models
Supervised Learning for LLM
Evaluation Metrics for LLM
Learning to Rank Algorithms
Optimization Techniques for LLM
Unit 3 • Chapter 5
Optimization Techniques for LLM
Summary
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Concept Check
What is an example of a common optimization technique used in LLM?
Decision Trees
Principal Component Analysis
Linear Regression
Gradient Descent
Which method is often employed to minimize loss functions in LLM?
Random Forest
Support Vector Machines
Logistic Regression
Stochastic Gradient Descent
What is a popular approach for hyperparameter tuning in LLM?
AdaBoost
Grid Search
K-Means Clustering
Naive Bayes Classifier
Which technique is used to prevent overfitting in LLM models?
Reinforcement Learning
Biclustering
K-Nearest Neighbors
Regularization
In LLM, what method involves updating model parameters based on minibatches of data?
Ensemble Learning
Gradient Boosting
Artificial Neural Networks
Mini-batch Gradient Descent
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Learning to Rank Algorithms