If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Design Thinking
(ML 11.4) Choosing a decision rule - Bayesian and frequentist
Choosing a decision rule, from Bayesian and frequentist perspectives. To make the problem well-defined from the frequentist perspective, some additional guiding principle is introduced such as unbiasedness, minimax, or invariance.
From playlist Machine Learning
Design thinking can improve anything from a water bottle to a community water system. See how design thinking improves the creative process, from Professor Stefanos Zenios: http://stanford.io/1mgkHGR
From playlist More
If you are interested in learning more about this topic, please visit http://www.gcflearnfree.org/ to view the entire tutorial on our website. It includes instructional text, informational graphics, examples, and even interactives for you to practice and apply what you've learned.
From playlist Graphic Design
In this video, you’ll learn how to broaden your definition of design through critical thinking, in order to see it in the world around you! Visit https://www.gcflearnfree.org/ to learn even more. We hope you enjoy!
From playlist Graphic Design
This video is brought to you by the Quantitative Analysis Institute (QAI) at Wellesley College as part of its Blended Learning Initiative. More information on the QAI's online resources can be found here: www.wellesley.edu/qai/onlineresources. To see more videos on applied statistics, chec
From playlist Applied Data Analysis and Statistical Inference
Time Series Model Selection (AIC & BIC) : Time Series Talk
How do we pick between several possible time series models? Code used in this video: https://github.com/ritvikmath/Time-Series-Analysis/blob/master/Model%20Selection.ipynb Data used in this video: https://github.com/ritvikmath/Time-Series-Analysis/blob/master/catfish.csv
From playlist Time Series Analysis
Introduction to Classification Models
Ever wonder what classification models do? In this quick introduction, we talk about what classifications models are, as well as what they are used for in machine learning. In machine learning there are many different types of models, all with different types of outcomes. When it comes t
From playlist Introduction to Machine Learning
What is Beauty in Design?: Understanding Design
Designers strive to fill up the world with beautiful environments, packaging, products and landscapes. These can be defined as aesthetic experiences wherein designers use the study of beauty to create pleasurable experiences for humans to interact with items and spaces. Join Prasad Borad
From playlist Understanding Design
“Choice Modeling and Assortment Optimization” - Session II - Prof. Huseyin Topaloglu
This module overviews static and dynamic assortment optimization problems. We will start with an introduction to discrete choice modeling and discuss estimation issues when fitting a choice model to observed sales histories. Following this introduction, we will discuss static and dynamic a
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
Predicting and Understanding Human Choices using PCMC-Net with an application to Airline Itineraries
Speaker(s): Alix Lheritier Facilitator(s): Omar Nada Find the recording, slides, and more info at https://ai.science/e/predicting-and-understanding-human-choices-using-pcmc-net-with-an-application-to-airline-itineraries--T7VHeDI6OAv0cXM7HWYT Motivation / Abstract The work focuses on pred
From playlist Recommender Systems
“Choice Modeling and Assortment Optimization” - Session I - Prof. Huseyin Topaloglu
This module overviews static and dynamic assortment optimization problems. We start with an introduction to discrete choice modeling and discuss estimation issues when fitting a choice model to observed sales histories. Following this introduction, we discuss static and dynamic assortment
From playlist Thematic Program on Stochastic Modeling: A Focus on Pricing & Revenue Management
Explaining by Removing: A Unified Framework for Model Explanation | AISC
Speaker(s): Ian Covert Host(s): Ali Al-Sherif Find the recording, slides, and more info at https://ai.science/e/explaining-by-removing-a-unified-framework-for-model-explanation--ao4ZaboI76dQLPhX40Bg Motivation / Abstract This work highlights the common patterns in 20+ different ML explan
From playlist Explainability and Ethics
This is part of a series of lectures on the Zermelo-Fraenkel axioms for set theory. We dicuss the axiom of chice, and sketch why it is independent of the other axioms of set theory. For the other lectures in the course see https://www.youtube.com/playlist?list=PL8yHsr3EFj52EKVgPi-p50f
From playlist Zermelo Fraenkel axioms
Mod-01 Lec-01 Definition of Game Theory and Rational Choice
Game Theory and Economics by Dr. Debarshi Das, Department of Humanities and Social Sciences, IIT Guwahati. For more details on NPTEL visit http://nptel.iitm.ac.in
From playlist IIT Guwahati: Game Theory and Economics | CosmoLearning.org Economics
Django Rest Framework & React Tutorial: Learning Management System (Blackboard / Moodle Clone)
In this intermediate Python Django tutorial you will learn to create a multiple-user system using React and the Django Rest Framework. We'll be building an online school where teachers can create assignments that students can complete and view their results. 💻 Clone this repo to get start
From playlist Django Tutorials
Re-Imagining the Social Sciences in the Age of AI - March 4, 2020
Re-Imagining the Social Sciences in the Age of AI: A Cross-Disciplinary Conversation Wednesday, March 4 5:30 p.m. Wolfensohn Hall Co-organized by the School of Mathematics and the School of Social Sciences, this public event will feature two short talks about the transformational possibi
From playlist Mathematics
Causal Behavioral Modeling Framework - Discrete Choice Modeling of Consumer Demand
There are increasing demands for "causal ML models" of the agent behaviors, which enable us to unbox the complex black-box models and make inferences or do proper counterfactual simulations. Many applications (especially in Marketing) intrinsically call for measurement of the causal impact
From playlist Fundamentals of Machine Learning
Foundations S2 - Seminar 3 - Skolemisation
A seminar series on the foundations of mathematics, by Will Troiani and Billy Snikkers. This season the focus is on the proof of the Ax-Grothendieck theorem: an injective polynomial function from affine space (over the complex numbers) to itself is surjective. This week Will started into t
From playlist Foundations seminar
System Design Interview: A Step-By-Step Guide
Learn something new every week by subscribing to our newsletter: https://bit.ly/3tfAlYD Checkout our bestselling System Design Interview books: Volume 1: https://amzn.to/3Ou7gkd Volume 2: https://amzn.to/3HqGozy ABOUT US: Covering topics and trends in large-scale system design, from th
From playlist System Design Interview