Data Modeling Tutorial | Data Modeling for Data Warehousing | Data Warehousing Tutorial | Edureka
***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations. Therefore, th
From playlist Data Warehousing Tutorial Videos
Learn the basics of how to code models in R as part of the boot camp for the Summer Institutes in Computational Social Science (with Duke Professor Chris Bail).
From playlist All Videos
(ML 13.6) Graphical model for Bayesian linear regression
As an example, we write down the graphical model for Bayesian linear regression. We introduce the "plate notation", and the convention of shading random variables which are being conditioned on.
From playlist Machine Learning
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
Statistical Modeling in Business Analytics with R | Edureka
( R Training : https://www.edureka.co/r-for-analytics ) A statistical model is a formalization of relationships between variables in the form of mathematical equations. A statistical model describes how one or more random variables are related to one or more other variables. The topics in
From playlist R Tutorial Videos
Model Theory - part 01 - The Setup in Classical Set Valued Model Theory
Here we give the basic setup for Model Theory. I learned this from a talk Tom Scanlon gave in 2010 at CUNY.
From playlist Model Theory
(ML 13.3) Directed graphical models - formalism (part 1)
Definition of a directed graphical model, or more precisely, what it means for a distribution to respect a directed acyclic graph.
From playlist Machine Learning
What is Math Modeling? Video Series Part 3: Making Assumptions
Mathematical modeling uses math to represent, analyze, make predictions, or otherwise provide insight into real world phenomena. After defining the problem statement, modelers must make assumptions to reduce the number of factors affecting the model. This episode brings us one step closer
From playlist M3 Challenge
(ML 13.4) Directed graphical models - formalism (part 2)
Definition of a directed graphical model, or more precisely, what it means for a distribution to respect a directed acyclic graph.
From playlist Machine Learning
Universality Classes of avalanches in sandpiles and growing interfaces by Deepak Dhar
PROGRAM :UNIVERSALITY IN RANDOM STRUCTURES: INTERFACES, MATRICES, SANDPILES ORGANIZERS :Arvind Ayyer, Riddhipratim Basu and Manjunath Krishnapur DATE & TIME :14 January 2019 to 08 February 2019 VENUE :Madhava Lecture Hall, ICTS, Bangalore The primary focus of this program will be on the
From playlist Universality in random structures: Interfaces, Matrices, Sandpiles - 2019
RubyConf 2016 - Metaprogramming? Not good enough! by Justin Weiss
RubyConf 2016 - Metaprogramming? Not good enough! by Justin Weiss If you know how to metaprogram in Ruby, you can create methods and objects on the fly, build Domain Specific Languages, or just save yourself a lot of typing. But can you change how methods are dispatched? Can you decide th
From playlist RubyConf 2016
Identifying Patterns in Animal Behavior (Lecture 2) by Claire Wyart and Gautam Reddy
PROGRAM ICTP-ICTS WINTER SCHOOL ON QUANTITATIVE SYSTEMS BIOLOGY (ONLINE) ORGANIZERS: Vijaykumar Krishnamurthy (ICTS-TIFR, India), Venkatesh N. Murthy (Harvard University, USA), Sharad Ramanathan (Harvard University, USA), Sanjay Sane (NCBS-TIFR, India) and Vatsala Thirumalai (NCBS-TIFR,
From playlist ICTP-ICTS Winter School on Quantitative Systems Biology (ONLINE)
Alison Heppenstall - Alan Turing Institute & University of Leeds, UK
Women in Data Science (WiDS) Turku 2021
From playlist Women in Data Science (WiDS) Turku 2021
At Scale Anomaly Detection for Enterprise Security: Joshua Neil, Microsoft
In this talk, Joshua will present a modular, scalable system for streaming anomaly detection for enterprise cyber security, along with some real user stories of such detections. Microsoft Defender Advanced Threat Protection is a suite of tools for enterprise defense. In particular, the E
From playlist Microsoft Defender: At scale anomaly detection for enterprise cyber defence Open configuration options
Structural Dominance Analysis of Dynamic Systems
To learn more about Wolfram Technology Conference, please visit: https://www.wolfram.com/events/technology-conference/ Speaker: Sergey Naumov & Rogelio Oliva Wolfram developers and colleagues discussed the latest in innovative technologies for cloud computing, interactive deployment, mob
From playlist Wolfram Technology Conference 2017
Lecture 1: Introduction and Overview I (14.13 Psychology and Economics, Spring 2020)
MIT 14.13 Psychology and Economics, Spring 2020 Instructor: Prof. Frank Schilbach View the complete course: https://ocw.mit.edu/14-13S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63Z979ri_UXXk_1zrvrF77Q In this first video, Prof. Frank Schilbach introduces the top
From playlist MIT 14.13 Psychology and Economics, Spring 2020
Tipping Points in Coupled Human-environment Systems by Madhur Anand
PROGRAM TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID) ORGANIZERS: Partha Sharathi Dutta (IIT Ropar, India), Vishwesha Guttal (IISc, India), Mohit Kumar Jolly (IISc, India) and Sudipta Kumar Sinha (IIT Ropar, India) DATE: 19 September 2022 to 30 September 2022 VENUE: Ramanujan Lecture Hall an
From playlist TIPPING POINTS IN COMPLEX SYSTEMS (HYBRID, 2022)
Systems Approaches for Combinatorial Biology - S. Chandrasekaran - 1/14/16
Bioinformatics Research Symposium Beckman Institute Auditorium Thursday, January 14, 2016
From playlist Bioinformatics Research Symposium
Stanford Seminar - How Behavior Spreads
EE380: Computer Systems Colloquium Seminar "How Behavior Spreads" Speaker: Damon Centola, University of Pennsylvania About the talk: New social movements, technologies, and public-health initiatives often struggle to take off, yet many diseases disperse rapidly without issue. Can the les
From playlist Stanford EE380-Colloquium on Computer Systems - Seminar Series
What is Math Modeling? Video Series Part 4: Defining Variables
Mathematical modeling uses math to represent, analyze, make predictions, or otherwise provide insight into real world phenomena. After defining the problem statement and making assumptions, defining variables tells modelers exactly the units they are looking for. This creates the basis for
From playlist M3 Challenge