'Practical problem' diaporamas de présentation

An Introduction to Process Improvement

1.17k views • 78 slides

Discrete Choice Modeling

William Greene Stern School of Business New York University. Discrete Choice Modeling. Bayesian Econometrics. Bayesian Estimation. Philosophical underpinnings: The meaning of statistical information How to combine information contained in the sample with prior information.

912 views • 77 slides

Inductive Classification

Inductive Classification. Based on the ML lecture by Raymond J. Mooney University of Texas at Austin. Sample Category Learning Problem. Instance language: <size, color, shape> size ? {small, medium, large} color ? {red, blue, green} shape ? {square, circle, triangle}

864 views • 72 slides

Javier Junquera

Fundamentals: the quantum-mechanical many-electron problem and the Density Functional Theory approach. Javier Junquera. Most important reference followed in the tutorial:. Most important reference followed in the tutorial:.

1.1k views • 56 slides

2.11k views • 55 slides

How Standards Interface with Curriculum and Instruction in Technology

680 views • 55 slides

The Perspective of Technology Education

The Perspective of Technology Education. The Second International Symposium on Educational Cooperation for Industrial Technology Education Kariya City, Japan. Presenter:. William E. Dugger, Jr. Senior Fellow International Technology Education Association (ITEA) & Emeritus Professor

607 views • 40 slides

Theories of Development

757 views • 37 slides

Cryptography and Network Security

Cryptography and Network Security. Sixth Edition by William Stallings . Chapter 2. Classical Encryption Techniques.

500 views • 37 slides

Goodness-of-Fit Tests with Censored Data

Goodness-of-Fit Tests with Censored Data. Edsel A. Pena Statistics Department University of South Carolina Columbia, SC [E-Mail: pena@stat.sc.edu]. Talk at Cornell University, 3/13/02 . Research support from NIH and NSF. Practical Problem.

372 views • 35 slides

Support Vector Machines

Support Vector Machines . More information can be found in http://www.cs.cmu.edu/~awm/tutorials. a. Linear Classifiers. x. f . y est. f ( x , w ,b ) = sign( w . x - b ). denotes +1 denotes -1. How would you classify this data?. a. Linear Classifiers. x. f . y est.

566 views • 33 slides

Qualifications Update: Practical Technology

418 views • 31 slides

458 views • 30 slides

Introduction to Child Development

967 views • 26 slides

Luis Alcazar Mechanical Engineering B.S. luis.alcazar@csueastbay.edu

CSU East Bay Engineering. Welcome to the World of Engineering. Luis Alcazar Mechanical Engineering B.S. luis.alcazar@csueastbay.edu. EDUCATION, Luis Alcazar. Napa Valley College Mechanical Engineering Transfer Class of 2002 UC Berkeley Mechanical Engineering, B.S. Class of 2005

455 views • 26 slides

501 views • 20 slides

A brief description of 8051 Microcontroller

318 views • 14 slides

B-Tree Index

B-Tree Index. B-Tree indexes are used to avoid large sorting operations. For example, a SQL query requiring 10,000 rows to be presented in sorted order will often use a B-Tree index to avoid the very large sort required to deliver the data to the end user. . B-Tree Example.

557 views • 14 slides

A brief history of steam engines

A brief history of steam engines. Evangelista Torricelli 1644 The barometer. Barometer

339 views • 12 slides

Scientific realism

Scientific realism. Varieties of (the problem of) realism. Ontological: is there a mind-independent world? Epistemological: can we know something about the world? Semantic: does language refer to the world, and are statements true or false mind-independently?

796 views • 10 slides