Loss function

Formal sciences
Statistics
Statistical inference
Mathematical statistics

Related lectures (31)

About
Privacy
Disclaimer

Graph Chatbot

Page 3 of 4

Neural Networks: Training and Activation

Explores neural networks, activation functions, backpropagation, and PyTorch implementation.

Maximum Likelihood Estimation

Explores Maximum Likelihood Estimation, covering assumptions, properties, distribution, shrinkage estimation, and loss functions.

Decision Trees: Regression and Classification

Covers decision trees for regression and classification, explaining tree construction, feature selection, and criteria for induction.

Multi-arm Bandits

Covers the exploration vs. exploitation dilemma in multi-arm bandits using the Upper Confidence Bound algorithm.

Mathematics of Data: Models and Learning

Explores models, learning paradigms, and applications in Mathematics of Data.

Implicit Functions: Advanced Analysis

Covers the advanced analysis of implicit functions, focusing on the application of the theorem of implicit functions.

Experimental Techniques: NMR & muSR - Kubo-Toyabe

Covers experimental techniques in NMR and muSR, focusing on asymmetry functions and relaxation functions.

Decision Theory: Risk and Hypothesis Testing

Covers decision theory, risk functions, and hypothesis testing in statistical inference.

Examples of decision models for Supervised learning

Covers examples of decision models for supervised learning, including regression, classification, ranking pairs, and sequence decoding for OCR models.

Linear Models for Classification

Explores linear models for classification, logistic regression, and gradient descent in machine learning.