Published on: 2024-12-30 04:33:29
Categories: 28
Share:
PCA & multivariate signal processing, applied to neural data, the period of training analysis, principal component PCA, and signal processing, and a few minor usable for data, the neural network is by Udemy is offering. This period, analysis techniques, and cutting data big data in neuroscience to you as theory training. Also, by learning how to code in more tutorials in the practice run.
The goal of this course. teaching methods of data analysis based on the matrix for the time series data in neuroscience, with an emphasis on methods to reduce the Multivariate and source-separation is.
Training offered includes Matrix Covariance analysis, principal component PCA, etc. mix vector, in particular, the analysis component can be independently. Although this course includes topics in the mathematics becomes difficult. But for people who have backgrounds math academic not also usable. From software more as the engine processing the numerical data used.
Publisher: : Udemy
Instructor: Mike X Cohen
Duration Time: 17h 34m
Number of lessons: 100 lessons in 12 sections
Language: English
Some linear algebra background (or interest in learning!)
Some neuroscience background (or interest in learning!)
Some MATLAB programming experience (only to complete exercises)
Interest in learning applied linear algebra
After the Extract with the Player your custom view.
Subtitles: English
Quality: 720p
Changes:
Version 2021/2 has not changed in number of courses and time compared to 2020/8, but it has been updated due to the passage of more than 6 months from the previous update
Version 2021/3 compared to 2021/2 has not changed in the number of courses and total time and has not been updated.
Version 2021/11 has increased by 20 lessons (2 sections) and 7.5 hours compared to 2021/2-2021/3.
– This course is free to download.
The 2024/11 version has not changed compared to 2021/11.
3.9 GB
Sharing is caring: