Certificate in AI Algorithms: Efficient Evaluation
-- ViewingNowThe Certificate in AI Algorithms: Efficient Evaluation is a comprehensive course designed to equip learners with essential skills in AI algorithms and their efficient evaluation. This course emphasizes the importance of selecting and applying appropriate algorithms for various AI tasks, as well as the critical role of efficient evaluation in ensuring the success of AI projects.
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โข Unit 1: Introduction to AI Algorithms
โข Unit 2: Types of AI Algorithms: Supervised, Unsupervised, and Reinforcement Learning
โข Unit 3: Evaluation Metrics for AI Algorithms: Accuracy, Precision, Recall, F1 Score, ROC Curve
โข Unit 4: Optimization Techniques for AI Algorithms: Gradient Descent, Stochastic Gradient Descent, Adam Optimizer
โข Unit 5: Regularization Techniques for AI Algorithms: L1 and L2 Regularization, Dropout
โข Unit 6: Bias-Variance Tradeoff in AI Algorithms
โข Unit 7: Ensemble Methods for AI Algorithms: Bagging, Boosting, Random Forests
โข Unit 8: Hyperparameter Tuning for AI Algorithms: Grid Search, Random Search, Bayesian Optimization
โข Unit 9: Deep Learning Algorithms: Convolutional Neural Networks, Recurrent Neural Networks, Transformers
โข Unit 10: Ethical Considerations in AI Algorithms: Bias, Fairness, and Transparency
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