- Видео 177
- Просмотров 56 346
Nick Stugard
Добавлен 28 май 2015
Making Language Mathematical: Why ChatGPT Works
In this video we discuss how we can define words as mathematical structures and what that looks like.
It's important to remember that applications like ChatGPT are just neural networks trained to predict the next most likely word.
For more details, please review my video on Neural Networks:
ruclips.net/video/8HHHIPwamIU/видео.htmlsi=hfJtpH_n3C7MhB53
And on Gradient Descent:
ruclips.net/video/Ipunmi6KraU/видео.htmlsi=A9-PdzA_vU2YOrxp
It's important to remember that applications like ChatGPT are just neural networks trained to predict the next most likely word.
For more details, please review my video on Neural Networks:
ruclips.net/video/8HHHIPwamIU/видео.htmlsi=hfJtpH_n3C7MhB53
And on Gradient Descent:
ruclips.net/video/Ipunmi6KraU/видео.htmlsi=A9-PdzA_vU2YOrxp
Просмотров: 104
Видео
What is Statistics? - Sampling and Bias
Просмотров 673 месяца назад
In this video we discuss how in statistics we want to describe a population, but we only have a sample. We talk about how this can go wrong and ways to prevent it going wrong, although we can never be perfectly confident.
What is Statistics? - Variables and Data Collection
Просмотров 1154 месяца назад
What is Statistics? - Variables and Data Collection
DS Lab 9 Jobs In Data with Sampling Distributions
Просмотров 657 месяцев назад
DS Lab 9 Jobs In Data with Sampling Distributions
9.2 DS - Simulations and Randomness in R
Просмотров 528 месяцев назад
9.2 DS - Simulations and Randomness in R
Limit Laws and Theorems
Просмотров 1138 месяцев назад
In this video, we learn the basic limit laws and rules as well as investigate the Squeeze Theorem
Investigating Limits with Technology
Просмотров 709 месяцев назад
How can we use a TI-83/84 calculator to evaluate functions to help us determine limits
Divergence and Curl
Просмотров 10411 месяцев назад
This video talks about the concepts, procedures, and applications of divergence and curl
Statistics - Chapter 10: Hypothesis Testing Examples
Просмотров 251Год назад
Statistics - Chapter 10: Hypothesis Testing Examples
Statistics - Chapter 10: Hypothesis Testing Concepts
Просмотров 270Год назад
Statistics - Chapter 10: Hypothesis Testing Concepts
Describing Regions in 2D
Просмотров 36Год назад
In this video, we talk about how we set up regions for our double integrals
More Matrix Multiplication - Identities and Inverses
Просмотров 42Год назад
More Matrix Multiplication - Identities and Inverses
Statistics: Chapter 8 - Sampling Distributions
Просмотров 1,1 тыс.Год назад
Statistics: Chapter 8 - Sampling Distributions
ML 14 - Convolutional Neural Networks Explained
Просмотров 118Год назад
ML 14 - Convolutional Neural Networks Explained
Creating a Convolutional Neural Network with Tensorflow
Просмотров 326Год назад
Creating a Convolutional Neural Network with Tensorflow
Great video! While playing around with the messages I found the model decided "we have been trying to reach you about your cars extended warranty" is ham haha. Other messages were no issue though.
where is the code file?
This was such a well explained video, thank you for this you are an amazing teacher!
Thanks for the kind words
Basics well explajned
Great technical delivery from your side, you easily made difficult topics easy and also connected dots wonderfully. Thank you a lot
I really hope someone will HELP me in my case so I built a similar spam detector for my college project but my professor is saying that it is a data science project that is why I want to give it a touch of cybersecurity so what should I add in this project to make it more specific to cyber security ?
Awesome Video Learned a lot
that was just awesome, love you from Azerbaijan Baku <3
Thank you for the kind words
Legend
Such a simple and greatly explained video. Thanks man
Can u please provide the code 🙂🙂🙂🙂
Hoe to deploy this plsss
Can you provide github project link containing full source code
Very interesting! Good recommendations.
Will you provide github project link For full souce code
hey there nice explanation Thanks a lot ! nicely explained and easy to understand wish we had professors like you in our college <3
very awesome video and demonstration! Insane to me how this works. one of those things as CS student that gets me excited!
jesus christ, talking about niche videos, tysm for this video!!!
Ha! So glad it helped!
Excellent
This is naive video, i understood whole concept in just 30 minutes. Thank you.
is this realated with cloud coumputing or general mails??/
This video details the algorithm we can use for classifying any text/string and is very general. But it is only a binomial classification with the only options being 'spam' or 'not spam.' This can be implemented inside of another program that inputs text/strings into this model we've built. Which means it could be implemented in a cloud computer setting or just for general emails.
Thank you man!
Awesome !!
It's not a bad project like this. To see the data loading and preparations step lined out is very nice. But I came here to learn about Naive Bayes and how those calculations work, and all I got was MultinomialNB().
Hi, thanks a lot for the video. It is very informative and very well explained. I have a curiosity, where did you get the email database from? Thank you in advance.
thank you, i can learn a lot from you
So I have gone through your entire videos And trust me as an engineering student you have awesome videos. But if you can focus your teaching with project based then you will have a lot of views Example the videos your have on linear regression, support vector machine and the rest But this is amazing Thanks so much
Thank you so much for the kind words and feedback. I'll have to make a new project video soon. Do you have any requests about a type of project I should do a video about in the future?
Hi there. Good video. Please, what screen record did you use ?
I used the free version of Logitech Capture
@@nickstugard9062 thank you
Thank you for making this video 😊
Great video mate, you stand out
please can you provide the link of written script
Thank you so much sir ☺️
why when i upload the dataset make this eroor Error tokenizing data. C error: Expected 2 fields in line 13, saw 4
Please can you link the dataset you used. Really good video btw. Very well explained.
Sorry for the delay. You can find the dataset I used in the description or here: github.com/NStugard/Intro-to-Machine-Learning/blob/main/spam.csv You can save it to your local machine by right-clicking the button that says "Raw," then "Save link as," then saving it as "spam.csv"
And thank you for the kind words
No problem at all. Thank you very much
Nicely explained... thanks
Thank you for the kind words
thanks, very good. What if there is new data outside the dataset, can it be detected? How to?
This was exactly what i needed
Highly underrated video. This channel is an undiscovered GEM!
🤔 What
waiting for more...😄
17:49 why is this cross product not the zero vector
When you do the minor matrix determinants, only the k-hat component will be zero.
I'm sold. Looks like I'm not done with Tunxis yet. lol
✍️
ow my brain
first
darn it
first
first
Thank you. Excellent!
Thank you Professor Stugard!Great resources ! Much appreciated