Machine Learning-Guided Treatment Discovery

Related lectures (31)

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Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.

Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

Explores generative and discriminative classification algorithms, emphasizing their applications and differences in machine learning tasks.

Explores machine learning for predicting new product life cycles and the challenges of limited historical data.

Showcases a project predicting Bitcoin's price using Twitter and ML, achieving 60% accuracy.

Explores feedback and adaptation in visual intelligence, enhancing machine performance in dynamic environments.

Explores linear regression in high dimensions and practical house price prediction from a dataset.

Examines the transformative impact of AI on engineering disciplines and the associated challenges.

Explores overfitting in polynomial regression, emphasizing the importance of generalization in machine learning and statistics.