Histrogram😊

Normal distribution or g l m😊

Thanks a lot!

Excellent lecture Jordan

13:09 Noise: 🚓 🚨

The dogo at 12:10 made it even a better lecture :)

Brown Jessica Perez Larry Rodriguez Matthew

Garcia Dorothy Rodriguez Brian Brown Larry

This is very good intuitive intro!

well explained.

Thanks 😊

Fabulous lecture. Everything is so clear! Thank you for making it available.

👍

informative :)

Mani pavi call Panna vaa attention Panna matiya true caler natrajen varum

Amazing job with introducing time-series relative to regression!

Thank you for your service 💞

I'm working on teaching myself about time series models from scratch, and your videos for L13 and L15 have been incredibly helpful, more than any other videos I've tried watching! Thank you so much for your explanations!

This is super helpful! Thank you so much! This is perfect for getting an overview for me, starting at the bare basics!

Cope

Hey Jordan I first want to say that your videos are great. They have helped me a lot! I also would like to add a small correction. Power frequency increases when supply > demand and decreases when demand > supply. The reason being that frequency is related to the rotational speed of the rotor. If the rotor has more mechanical power input (supply) then the speed increases ( Power = Torque X Angular Velocity). The increase in speed increases the AC frequency. In the case of higher load an electromagnetic opposition to rotation is experienced by the rotor and the speed starts to decrease leading to lower AC frequency.

Thank you! This is the kind of video I was looking for

Great explanation and illustrations! Thank you.

Very useful video, well explained and illustrated. Thank you very much for making it available to the wide audience :)

Incredible work. I learned so much - thank you!

Incredible lecture. Thank you so much.

Great lecture! Examples of time series analysis (mostly biomedical - EEG): www.youtube.com/@bionichaos/videos

Thanks for sharing this information. Comprehensive concepts intro and easy to understand. Great for my job project at this moment.

#amflearningbydoing #amflearning this awesome bro, thanks a lot

@Jordan Kern Do you recommend any reading material to accompany your wonderful lectures?

Great job 😍

Swept are is not relevant to wind turbines as the wind pushes what it touches and can not push on the gaps between the blades there are three things that are fixed and that do not change 1 the diameter 2 the total area of the gaps between the blades and 3 the total wind contact area of the blades weather moving or still ,Wind has no kinetic energy it has force Mv squared kinetic energy is the energy of consistent work from a consistent force . Betz limit is an insult to engineers regards Graham Flowers

Betz limit has been smashed and debunked by the gyro wind turbine regards Graham Flowers

Helped me understanding a lot more than in my lecture! Thank you very much for creating this great content

Hi Jordan - how do you produce the last plot you showed with relative variance vs. frequency?

Amazing 👍

Hi Mr jordan Sorry, is there a pdf file for this topic that I need?

I still don’t understand

Excellent introductory lectures (along with 13) ! Many thanks

Watching this before my candidacy exam... thank you!

The material machine tentatively greet because hour clearly knock next a longing stove. goofy, adventurous oyster

great video!!! Can u share slides, it will be nice!!!!!

Excellent lecture! Chapeau!

Best lecture in time series so far

great work

So much for professors who like inflicting pain on student subjects by presenting these concepts in a convoluted way. Like if it's an esoteric black magic.. Step bey step crystal clear ! Thank yo and Bravo!

bad audio

Thank you, and by the way 11:49 there's a clear trend on a first graph indicates about Batman existence!

Today I presented my master's thesis proposal on univariate forecasting (time series forecasting). I intend to combine different models such as Holt Winters, ARIMA, LSTM neural networks, random Forest, etc...The Synods told me that time series forecast are simple and less accurate than multivariate forecast... any advice to answer them? ?

But lecture 14 ain't available, nice explanation though