123 Ways to Add Pizazz to a Panel Discussion

123 Ways to Add Pizazz to a Panel Discussion

  • Downloads:9706
  • Type:Epub+TxT+PDF+Mobi
  • Create Date:2021-04-07 11:51:28
  • Update Date:2025-09-06
  • Status:finish
  • Author:Kristin Arnold
  • ISBN:0967631386
  • Environment:PC/Android/iPhone/iPad/Kindle

Summary

Add some pizazz to the traditional panel discussion format with these tips and techniques。

Drawn from her extensive experience as a nationally recognized speaker, master facilitator, and panel moderator, Kristin Arnold provides 123 different ways to transform a traditional panel discussion into the hit of your conference! In this 200+ page reference guide, you discover myriad ideas to punch up your panels including how to:





Design an inspiring panel format
Find and prepare your panelists
Curate fabulous questions
Set the stage and A/V tips
Open with pizazz!
Inspire spontaneous and informative conversations
Intervene firmly but tactfully
Finish with panache
Keep the audience at the edge of their seats
Shift gears periodically
Engage & involve the audience
Moderate lively audience Q&A
PLUS tons of tips on how to adapt these techniques to the virtual environment!



Just pull out this quick reference guide to provide a little inspiration for your live, face-to-face, virtual, and hybrid panel discussions!

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Reviews

Nadiantara Wayan

Perfect and free, what else do you want?

SalKhan

A must read for beginners in machine learning!

محمد

Remarkable!I don't regard this one as an introductory book, but rather a "refresher" on the base of mathematics required for machine learning。 Most of the book was a delight to read, I liked the slow building up of ideas in first chapters such as vector spaces, linear independence, basis, rank, linear mapping, inner products, orthogonality, 。。, etc。 to the point that you become comfortable with them when used in more complex chapters, even if you had little or no background on them。There were so Remarkable!I don't regard this one as an introductory book, but rather a "refresher" on the base of mathematics required for machine learning。 Most of the book was a delight to read, I liked the slow building up of ideas in first chapters such as vector spaces, linear independence, basis, rank, linear mapping, inner products, orthogonality, 。。, etc。 to the point that you become comfortable with them when used in more complex chapters, even if you had little or no background on them。There were so many "Wow!"(s) moments, like geometrical interpretation of singular value decomposition, treating correlation as an inner product between two random variables, principal components as the eigenvalues and eigenvectors of data covariance matrix, latent variable perspective and many more。。Not to mention the amazing formatting, beautiful LaTeX and gorgeous figures that made me envious sometimes, for example:Yet, some parts were not easy to grasp (or I completely skipped, like dual Lagrange optimization), and the Probability and Distributions chapter will be very hard to read without prior "wink ;)" knowledge on probability。In general I really liked it and very much recommend it! 。。。more

Filip Karlo Došilović

If there is a book to start your machine learning journey the right way, whether you are a mathematics or computer science student, this would be it。A piece of advice: I would not recommend reading this book if you did not have exposure to calculus, introductory linear algebra and probability theory。 You should view the first part of the book as a quick refresher, and not as an introduction to these subjects。

Tianyao Chen

A great crash course to brush up the math required for ML!

Estefano Palacios

Brilliant and PreciseThe book is the missing piece between books like Artificial Intelligence: A Modern Approach and mathematics。 It is recommended that you've had exposure to the mathematical topics prior to reading the book, but let that stop you if you're a beginner。 Having said that, a course on single variable calculus ought to be under your belt。 Brilliant and PreciseThe book is the missing piece between books like Artificial Intelligence: A Modern Approach and mathematics。 It is recommended that you've had exposure to the mathematical topics prior to reading the book, but let that stop you if you're a beginner。 Having said that, a course on single variable calculus ought to be under your belt。 。。。more

Robin Dong

Just give this book a preliminary view。It's easy to understand for most parts hence good for software developers (such as me) Just give this book a preliminary view。It's easy to understand for most parts hence good for software developers (such as me) 。。。more

Nick Greenquist

Very difficult mathematics book。 However, I feel like I came out the other side with some new mathemetical skills in my toolbox and a better understanding of the theory behind many machine learning algrorithms。 However, this book is definitely a very tough read。

Ariyasacca

awesome

Solomon Xie

I'm so intimidated by the enormous amount of terms and symbols, and couldn't say it's a beginner friendly book。 So i'm gonna let go of this and try other books I'm so intimidated by the enormous amount of terms and symbols, and couldn't say it's a beginner friendly book。 So i'm gonna let go of this and try other books 。。。more