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Gracias por compartir su conocimiento, casi no hay videos donde expliquen detalladamente 👍

Thanks for the great video. Very clear explained. I love that you made the code available, but I have trouble reaching the website it is posted on. Can this be due to the country I am reaching it from? And can the code be found in another location?

Hello, I am trying to access your website, but it has been down for the last two days. I am also trying to access the Python scripts you mentioned for data processing. Could you help me with this?

Very good & clear explanation. Thanks.

thank you for your very clear explanation. It helps me a lot

Битый час видео ни о чем, на внимательный просмотр ушло двое суток. Пересказ общих фактов о PLS-DA из википедии. Если кто не знал узнает про ложно позитивные, ложно негативные, истинно позитивные, истинно негативные ответы, некоторые числовые характеристики для оценки качества разных моделей, причем с ошибками в формулах. Ссылок на примеры бесплатных программ или готовых скриптов реализующих PLS-DA тут не дается. В конце конкретно упоминается лишь американский спектрометр ATR-FTIR для идентификации "кокаинуума", взрывчатки, и лазерный спектроскоп отпечатков пальцев, видео похоже больше как реклама его возможностей для далеких от математики богатых таможенников.

el matlab lo consigues gratis en tutoriales de yt y minitab igual, USE PAST SOFTWARE LIBRE PARA HACER PCA peor tiene pocas opciones como para escoger el tipo de metodo de calculo

I also mention Orange. It is a Python-based free software and it has a Spectroscopy add-on, which is excellent for the spectra visualization & preprocessing. The respective tutorials are encountered in RUclips too.

Hola no me quedo claro como van nombrados los autores? Jeanpierre es el apellido? D? Valentín ?Acevedo?. Gracias.

Que buen video que bien explicado!!!

Hello , thank you for this nice video , for the scattering , you mentioned that one of reason for scattering is the molecule not at the same distance , so how can i make the molecule at the same distance if i prepared as example solution contain dye dissolved in water , i prepared different concentrations then i measured spectra for them and i got scattered for the data, thank you.

Good quality content

Awesome!

L = Light is A = Amplified by the S = Stimulation of the E = Emissions of R = Radiation = LASER is a DEVICE. Then a Stream of PHOTONS are shot out of the LASER DEVICE...so it is NOT what you said. A beam of light...NO..its a stream of photons. A LASER is a DEVICE a stream of PHOTONS is what happens so the way that you described it is kind of correct but in Pyhsics we don't do KIND OF... There are 2 parts to this SYSTEM.

I like so much the video, but I'd to see when you use the validation and load test data. Is there a video like this?

am ok with data normalization (i.e., scaling), however I have a doubt concerning to the importance of DP methods for modeling!

For comparing 2 group, we can coded group to +1 and -1. If I have more than 2 group, let say 3 group, how i am going to coded? Please give some examples

can anyone point for me places to download spectral data for my research?? i am lokking for bearings spectrum data

Professor, which one from the programs you've mentioned on the video that can "mass" preprocess spectra? like can do multiple spectra in one touch Thank you

How I can see the equation of PLS models? Is there a specific setting?

Muy claro. Felicitaciones!!! y Gracias por subirlo

does this work on crystal structure as well?

Thank you so much for this informative and well-explained session. I have been trying to write some code in MATLAB to perform MSC, could you please help with a script to execute that? Thanks

Good

Man. I just found out that I need to preprocess my data for MSC, this channel has really helped me. Thank you for the good job!!

helpful

Super technical presentation on QCL perhaps the best on internet

Thank You! Such a good tutoial!

a very good explanation 👍👍

Hola Edwin, fue una excelente presentación. Sin embargo, me gustaría que realizaras un video, donde uses el PCA, pero haciendo énfasis en algún problema de negocios. Saludos

How can this be useful in chemometrics

Wow that is awesome!!! The only point is the voice quality but your content and your presentation was awesome. Thanks a lot

me gustaria que hicieran un curso completo de quimiometria, seria genial

Buenas tardes seria bueno que esots videos tambien los compartieras en español

buenos dias seria bueno que compartieran todos estos temas de quimiometria en español tambien estoy muy interesado en seguir aprendiendo de estos temas.

Thank you so much ! I've been looking for these types of information for weeks. This is so far the mos informative stuff I watched. I just need to get how to apply it with R now hahaha. (Forest scientist trying to work with spectral data here).

Hello, an excellent video. The best explanation of spectral preprocessing techniques I've seen in years. Taking advantage of the occasion, I have a question that I would appreciate if you would help me by clarifying it. All these current techniques are on the spectra individually (rows), but in the literature, I find other techniques, such as mean centering, auto-scale, and variance scale, among others, that act on the variables (columns). In some manuals, I found the latter necessary because several multivariate algorithms compute results driven by variance patterns in the independent variables. Specifically, my question is: When to use tools such as mean centering, auto-scale, and variance scale, or are they already integrated into techniques such as PLS?

Hello! Thank you! The best video in the net on data pre-processing I found so far! In Unscrambler, when you run the PCA based on the original data, you have the choice to select mean centering, which I think is meant to get rid off scattering. Would you in all,cases preprocess data with SNV and maximum centering?

Thank you for your attention! Comments? Suggestions? Recommendations? All options are welcomed!

Thank you for your attention! Comments? Suggestions? Recommendations? All options are welcomed!

Thank you for your attention! Comments? Suggestions? Recommendations? All options are welcomed!

Gracias por el vídeo Me ayudó mucho para el análisis de mi trabajo de grado Excelente

Thank you for your attention! Hope that you all liked the video. Comments? Suggestions? Recommendations? All options are welcomed!

Gracias por su atención! Espero que les haya gustado el webinar. Comentarios? Sugerencias? Recomendaciones? Todas las opciones son bienvenidas!

Amazing!!!

Thank you for your attention! Hope that you all liked the video. Comments? Suggestions? Recommendations? All options are welcomed!

Gracias por su atención! Espero que les haya gustado el webinar. Comentarios? Sugerencias? Recomendaciones? Todas las opciones son bienvenidas!

Thank you for your attention! Hope that you all liked the video. Comments? Suggestions? Recommendations? All options are welcomed!

Gracias por su atención! Espero que les haya gustado el webinar. Comentarios? Sugerencias? Recomendaciones? Todas las opciones son bienvenidas!