Відео

punch the keyboard a little faster

oh,Thank you so much! It has helped me a lot when I was desperately seeking tutorials! May I ask you another questionDo all subjects have to have the same SNRthresh valuefor example,all set to 6,or can it be adjusted according to the data situation of each individual subject?

Why in the Fisher test we calculate all different contingency tables? What's the purpose of doing that?

Thanks a lot. I found what I was searching for badly.

this was indeed helpful, thanks John

Thanks man

Helped me Thanks

thank u i really needed this

2024 in Canada, still useful :) One question I do have, is *why* the delta OD tranformation is done before the other preprocessing and analysis stages. You do mention that if we didn't do this we'd have to calculate a partial pathlength factor (not sure why that is), but I don't quite understand why. When we do the regression, we're looking at change over time in relation to e.g. the timing of our conditions. Why do we want to change that to looking at the *relative* change in time? Is it essentially just to scale the data?

thanks, quite clear

This is great, covering almost all different possibilities and scenarios. Given the value that meets a condition, let me say, nlargest, how to easily retrieve its corresponding index?

Hi, Jonathan, I have a trouble about Homer2, error that'The length of PPF must match the number of wavelengths in SD.Lambda', and what should I do? Could you help me, thanks for you time and consideration.

Sir I amm getting error while loading dataset, URLError:<urlopen error [WinError 10061] No connection could be made because the target machine actively refused it>

What a relief to see this fantastic video on the question I've been asking myself for months!

How to get the exact location or position of values?

Hi, I have a question about AtlasViewer : When I design a probe, I cannot add the springs, when I add the springs, the modifications are not saved. I have successfully added the anchored points but I have a problem with the springs. Thank you very much for your response.

With regards to line 13, what would you do if you wanted to display a range of values? For example, display all rows, where the dinner bill was between 15 and 30?

Awesome!! Clear and easy to follow. +1 Subscriber

Thank you ❤❤

Solved my problem! Thanks! Would have appreciated to have the script as well! <3

Great video! It's very helpful. Many thanks. I've noticed that sklearn has a 'Permutation feature importance' function. Will do the trick?

i am getting curious error to me: when i define train_df = df.iloc[train] i get error: TypeError: unhashable type: 'numpy.ndarray'......

Awesome video. Thank You.

Thanks man!

Nice tutorial! thanks for posting this

Sir did you have any ppt or report in this project did you have pls send me sir

How about an writing an iterative function to do for a large dataset with large number of columns

Hi Jonathan, do you know how to exclude bad channels using the NIRS toolbox? I can't find an answer to that anywhere. I am not managing to do it properly calling any Homer function or if I do it, even using my own code, I can't run the GLM in the NIRS toolbox, probably because the number of channel becomes uneven

Mesej yang jelas, struktur yang jelas, mudah difahami, terima kasih

Lost...

Your content is so touching

Could you please share which video covers the process for calling Homer2 in the NIRSToolbox - so that we can run Run_Homer2?

I was wondering what the t-statistic means for if I only have one beta value for each channel. For example, if I just have one trial data for one subject included 10 repeatations, I could get the beta by GLM. I see many papers, they said the t-statistic is calculated by t = c'*beta/(c'*cov(beta)*c), but if the beta's dimension is 2*1 (2 is the number of regressors and 1 is a channel), what is the cov(beta) stands for?

Your videos are so important to me, as a self-learner researcher. Thank you so much!

the sound is not good I am quite disappointed

what happens if we have more columns ?do we need to repeat the same process several times?

hats off to you :)

so touching for an excellent video

hey, would it be possible to share the code in the description

the sound is not good I am quite disappointed

really helpful video thank you.

Hey @Jonathan Perry.. Thanks for this nice video. I am subscribing your channel. cheers.. Keep posting awesome content

dear Sir are u able to use CNN for regression issue , I get stuck that point in my project ‘could u please give me hands? I appreciate it

Thank you Jonathan. I watched it to the end. I understood that I know nothing.

Thank you very much sir, very informative basics.! Highly encourage you for the future!

Vector is as well as variable , isn't it?

from sklearn.model_selection import train_test_split X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.2, random_state=1)

Any chance you would do a video specifically for data pre processing on a csv file with a handful of features? Thank you!

very useful, but are you able to upload a higher quality version i find it hard to read all the slightly blurred text for a long time. Great content though.

Thanks for sharing knowledge, this video helped me , keep Posting content! Best of luck for future!