This is an introductory-level course in supervised learning, with a focus on regression and classification methods. The syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (...
The course CS231n is a computer science course on computer vision with neural networks titled “Convolutional Neural Networks for Visual Recognition” and taught atStanford University in the School of Engineering This course is famous for being both early (started in 2015 just three years after...
Syllabus Introduction, Empirical Background and Definitions Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions Background, Definitions, and Measures Continued Homophily, Dynamics, Centrality Measur...
This is the only course at Stanford whose syllabus includes nearly all the math background forCS 229, which is whyCS 229andCS 230specifically recommend it (or other courses resting on it).Prerequisite:Math 21or equivalent. CS 106A:Programming Methodology Introduction to the engineering of comput...
Syllabus Introduction and Descriptive Statistics for Exploring Data This module provides an overview of the course and a review of the main tools used in descriptive statistics to visualize information. Producing Data and Sampling In this module, you will look at the main concepts for sampling and ...
Syllabus Introduction Welcome to Machine Learning! In this module, we introduce the core idea of teaching a computer to learn concepts using data—without being explicitly programmed. The Course Wiki is under construction. Please visit the resources tab for the most complete and up-to-date informat...
Syllabus Unit 1 - Introduction Unit 2 - Propositional Logic Unit 3 - Relational Logic Unit 4 - Functional Logic Unit 5 - Conclusion Taught by Michael Genesereth Tags united states Related articles 150+ Stanford On-Campus Computer Science Courses Available Online ...
Syllabus 1 Unit 1 introduces the course and reviews key principles of effective writing. In particular, you will practice cutting clutter from writing. 2 Unit 2 focuses on writing with strong, active verbs. Lessons include how to: write in the active voice; avoid turning verbs into nouns; cho...
This course is offered as part of the Georgia Tech Masters in Computer Science. The updated course includes a final project, where you must chase a runaway robot that is trying to escape! Syllabus Localization Localization,Total Probability,Uniform Distribution,Probability After Sense,Normalize Distr...
More specifically, thesyllabusoutlines the following topics as being treated: Understanding machine learning production Understanding machine learning systems design Data engineering Model development Model evaluation Experiment tracking Deployment Model scaling ...