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Nick Stugard
เข้าร่วมเมื่อ 28 พ.ค. 2015
What is Statistics? - Sampling and Bias
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.
มุมมอง: 51
วีดีโอ
What is Statistics? - Variables and Data Collection
มุมมอง 883 หลายเดือนก่อน
What is Statistics? - Variables and Data Collection
DS Lab 9 Jobs In Data with Sampling Distributions
มุมมอง 635 หลายเดือนก่อน
DS Lab 9 Jobs In Data with Sampling Distributions
9.2 DS - Simulations and Randomness in R
มุมมอง 506 หลายเดือนก่อน
9.2 DS - Simulations and Randomness in R
Limit Laws and Theorems
มุมมอง 887 หลายเดือนก่อน
In this video, we learn the basic limit laws and rules as well as investigate the Squeeze Theorem
Investigating Limits with Technology
มุมมอง 687 หลายเดือนก่อน
How can we use a TI-83/84 calculator to evaluate functions to help us determine limits
Divergence and Curl
มุมมอง 10310 หลายเดือนก่อน
This video talks about the concepts, procedures, and applications of divergence and curl
Statistics - Chapter 10: Hypothesis Testing Examples
มุมมอง 22911 หลายเดือนก่อน
Statistics - Chapter 10: Hypothesis Testing Examples
Statistics - Chapter 10: Hypothesis Testing Concepts
มุมมอง 24411 หลายเดือนก่อน
Statistics - Chapter 10: Hypothesis Testing Concepts
Describing Regions in 2D
มุมมอง 3611 หลายเดือนก่อน
In this video, we talk about how we set up regions for our double integrals
More Matrix Multiplication - Identities and Inverses
มุมมอง 37ปีที่แล้ว
In this video I describe what identities and inverses are. I also show how to use these concepts to solve other types of problems.
Statistics: Chapter 8 - Sampling Distributions
มุมมอง 888ปีที่แล้ว
Statistics: Chapter 8 - Sampling Distributions
ML 14 - Convolutional Neural Networks Explained
มุมมอง 117ปีที่แล้ว
ML 14 - Convolutional Neural Networks Explained
Creating a Convolutional Neural Network with Tensorflow
มุมมอง 312ปีที่แล้ว
Creating a Convolutional Neural Network with Tensorflow
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