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[ FreeCourseWeb ] Skillshare - LaTeX for Data Scientists 2020 (and for non-Data Scientists also)

Torrent: [ FreeCourseWeb ] Skillshare - LaTeX for Data Scientists 2020 (and for non-Data Scientists also)
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[ FreeCourseWeb.com ] LaTeX for Data Scientists 2020 (and for non-Data Scientists also)

Download More Latest Courses Visit -->> https://FreeCourseWeb.com



MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 19 Lessons (2h 13m) | Size: 620.9 MB
If you are here, that's because you want to learn LaTeX, the best document preparation system out there! With LaTeX, you can create professional documents and presentations. If you are a student, researcher, Data Scientist, or any kind of scientist or professional in general, then it's not bad idea if you have things documented with LaTeX. Yes, every scientist or engineer needs to know math, and there isn't anything better for writing math than LaTeX.

Documenting your ML or DL model in a Jupyter Notebook? LaTeX.

If you are going to present something in a very important conference? LaTeX.

Already doing your thesis? LaTeX.

Use Winrar to Extract. And use a shorter path when extracting, such as C: drive

ALSO ANOTHER TIP: You Can Easily Navigate Using Winrar and Rename the Too Long File/ Folder Name if Needed While You Cannot in Default Windows Explorer. You are Welcome ! :)


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We upload these learning materials for the people from all over the world, who have the talent and motivation to sharpen their skills/ knowledge but do not have the financial support to afford the materials. If you like this content and if you are truly in a position that you can actually buy the materials, then Please, we repeat, Please, Support Authors. They Deserve it! Because always remember, without "Them", you and we won't be here having this conversation. Think about it! Peace...

Downloads: 60
Category: Other/Tutorials
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Added: 2020-06-02 11:01:31
Language: English
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Release name: [ FreeCourseWeb ] Skillshare - LaTeX for Data Scientists 2020 (and for non-Data Scientists also)
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