Lecture 1: Introduction to Information Theory

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Information Lecture 1: Introduction to Information Theory

Title	:	Lecture 1: Introduction to Information Theory
Lasting	:	1.01.51
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Great stuff Thanks very much
Comment from : @donaldwhittaker7987

Thank you, Prof David McKay!
Comment from : @jialinliu0817

David McKay was a brilliant teacher The first 8 lectures on Information Theory are the best available The other 8 lectures are also great For the same material in more detail, I bought the book It too is outstanding (except the print is too small)
Comment from : @MichaelKohn-v5z

Absolutely one of the gems that are just there on the internet but hidden by some bullshit coursesbrWe should keep digging to find more of these!
Comment from : @mahmoudehab8627

Could anyone explain how is the flip pobability is 10^-13 and and 1 failure is 10^-15 Video reference is at 22:10
Comment from : @gadepalliabhilash7575

🎉
Comment from : @dharmendrakamble6282

2:00
Comment from : @SphereofTime

I'm a bit curious about when these Lectures were recorded Was it 2003??
Comment from : @AtharvSingh-vj1kp

what an amazing lecture and great teacher May you rest in peace You will not be forgotten
Comment from : @a_user_from_earth

After listening to this lecture, my IQ went up 20 points!
Comment from : @artmaknev3738

J'ai compris pourquoi répéter 3 fois la même information de suite à mes enfants n' était pas forcément efficace :-)
Comment from : @christopheguitton7523

towards 56:00 he uses the term "bit error" and "block error" but doesnt define them properly
Comment from : @sahhaf1234

channel immigration
Comment from : @박재우학부재학전기전

RIP prof David, you were, and still a great inspiration to us
Comment from : @mohamedrabie4663

I looove the lectures! Thank you for the upload!
Comment from : @jedrekwrzosek6918

This is a great lecture The design of case problem is really helpful here Thanks for the lecture
Comment from : @fireflystar5333

Information theory
Comment from : @dharmendrakamble6282

34:43
Comment from : @GOODBOY-vt1cf

32:13
Comment from : @GOODBOY-vt1cf

15:52
Comment from : @GOODBOY-vt1cf

13:24
Comment from : @GOODBOY-vt1cf

9:50
Comment from : @GOODBOY-vt1cf

3/8 3/8 2/8 cake and siblings brbrThat's the most equal way to share brIn the 3rd cake they are most close to equalbr4/82/8 2/8 is far behind equal
Comment from : @papatyavanroode2329

hey is there any pre-requisite of it
Comment from : @keshavmittal1077

This is great, thank you! The lecture is far more entertaining than just reading the book
Comment from : @TheNiro87

I am curious to know how Shannon would have interpretted the internet as part of his theory noise perhaps
Comment from : @terrythibodeau9265

"People need 20 GB drives nowadays" Laughs in Call of Duty
Comment from : @Rockyzach88

These lectures are great Thanks for sharing
Comment from : @leduran

Hi, I just wanted to ask what was meant when at 24:20 when he says that "1 is the same as 5, and if there was a 4, there would be a 0"
Comment from : @vedantjhawar7553

Profesor McKay is certainly extremely competent in the subject but this really is the most un-intuitive way of introducing information theory We are given the answer right from the start and work our way backwards to see that it is an effective system, instead of trying to understand the problem and find the adequate solution We are never trying to understand the nature of the problem but instead made to test the effectiveness of the solution Typical of classical academic philosophy Let's make knowledge as boring and abstruse as possible so the riff raff is kept out of our little club!
Comment from : @tonewreck1

can someone explain how to solve the homework problems?
Comment from : @driyagon

I like this channel I'm already teaching this topic for student in Iraq In Arabic
Comment from : @dralaaal-ibadi8644

One of the best lecture of " information theory and coding " I have ever seenlove from India 🇮🇳🇮🇳🇮🇳🇮🇳
Comment from : @the_anuragsrivastava

Repetition (redundancy) is dual to variation -- music brCertainty is dual to uncertainty -- the Heisenberg certainty/uncertainty principle brSyntropy (prediction) is dual to increasing entropy -- the 4th law of thermodynamics brRandomness (entropy) is dual to order (predictability) -- "Always two there are" -- Yoda brTeleological physics (syntropy) is dual to non teleological physics brDuality: two sides of the same coin
Comment from : @hyperduality2838

What are the requirements to understand this lecture?
Comment from : @carloslopez7204

Thanks for these
Comment from : @deeplearningpartnership

This is fantastic I love it
Comment from : @qeithwreid7745

at 46:50, what is rate? i guess it is (1/no of repetitions) but what does it mean in layman terms
Comment from : @drumshhrum

I have read the extraordinary book
Comment from : @minglee5164

This may be the longest blackboard I've ever seen
Comment from : @AvindraGoolcharan

8:22
Comment from : @alyssag8099

Thank you professor
Comment from : @ciceroaraujo5183

So nice to watch a video like this that does not have music
Comment from : @george5120

Binomial is more related to probability topics Bernoulli is about hydraulics
Comment from : @MDAZHAR100

Thank you for a great lecture, looking forward to follow the rest and study the book!
Comment from : @oscarbergqvist4992

00:30 Information Theory invented by Claude Shannon to solve communication problems Fundamental problem: Reliable communication over an unreliable channel eg [Voice->(Air)->Ear], [Antenna->(Vacuum)->Mars Rover], [Self->(magnetized film)->Later Self]br04:00 Received signal is approximately equal to the transmitted signal because of added noisebr05:45 What solutions are there for having received and transmitted signal be the same? Either physical solutions or system solutionsbr07:30 Source message -> [Encoder] -> Coded transmission -> [Channel (noise introduced)] -> Received message -> [Decoder] -> Best guess at original sourcebr08:45 Encoder is some system that adds redundancy Decoder makes use of this known system to try to infer both the source message and n
Comment from : @AlexandriaRohn

im learning this at school yet I'am here watching a lecture on Youtube I dont know why I should pay attention in my class I guess
Comment from : @izzyr9590

Thank you, Thank you, Thank you for sharing these excellent video lectures Dr Mackay is amazing at teaching complicated topics These lectures are great supplement to his excellent book on information theory which has so many excellent plots and graphs that enables one to visualize information theory Information theory comes alive in pictures Thank you for sharing these
Comment from : @IrfanAli-jl7vb

Dr Mackay is a great explainer Anyone interested in machine learning and Bayesian statistics can also read his doctoral thesis
Comment from : @linlinzhao9085

Genius camera work
Comment from : @palfers1

There is no information here and when will it be realized?Never!!!
Comment from : @jabbatheplutocrat1074

Helpful lecture
Comment from : @motikumar1442

awesome example of teaching style
Comment from : @reyazali2768

I'm fairly new to this What is a "flip" ?
Comment from : @mustafabagasrawala7790

I don't mind the slowness With some decoding, my brain is receiving a cleaner signal with that extra redundancy
Comment from : @baganatube

You know he's a jokster cuz at 1:00:13 the slide says his textbook weighs "35 lbs"
Comment from : @pauldacus4590

Thank you for these great lectures your memories will live on RIP
Comment from : @dragonfly3139

rip david
Comment from : @circlesinthenight3141

Good lecture except for the highly distracting camera work
Comment from : @stevealexander6425

How am I just now discovering this lecture series??! This is awesome!
Comment from : @JerryFrenchJr

It was amazing, Finally I learned Shannon noisy channel theorem: there is exist an encoding and decoding system that could reach to the capacity of channel so error correcting and detecting course is about to learn these encoding and decoding system wowbrAmazingbrlots of thanks to the teacher
Comment from : @monazy11

the fact is the received signal is not identical to sent signal due to corruption and distortion in the signal, in a process , so how much of the the original signal is received ,what would be the measurement in what unit ,,,,,thats why i do drugs ,and dont give a damm !
Comment from : @GSSIMON1

I was saddened to read that David MacKay passed away earlier this year
Comment from : @iwtwb8

I am not involved in information technology but this lecturer is making a difficult subject like information theory look so easy You really must see this
Comment from : @lesliefontenelle7224

I would use SUDOKUS for communicationbrOnly few numbers have to be transmitted correctly, and the other numbers/information can be restored by the decoder :-D
Comment from : @Handelsbilanzdefizit

This is painfully slow I'm sure the information is fantastic but you have to watch him write everything he says on the chalkboard When I got to him telling the class to discuss how much 10 of 10,000 is I couldn't take it anymore Can anyone suggest a similar lecture that moves more quickly?
Comment from : @PseudoAccurate

Was Mr Bionomial a joke that fell on dead ears or was it a genuine confusion with Bernoulli?
Comment from : @turkiym2

this really helps I really wanted to learn information theory this video series is really easy to understand and awesome
Comment from : @abhishekpal5871

very great theory
Comment from : @ncckdr

Cheering, in these days of advanced educational gizmolgy, to see Professor MacKay making extensive and effective use of a stick of chalk and a polychromatically absorbent surfaced boardbr{Tyneside, England]
Comment from : @spring74light