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Git, GitHub, and GitLab: From Beginner to Expert


On this course, we first clarify the fundamental working precept of the distributed model management software program Git. Then, we clarify the star options of Git: branching and merging. We’ll see how branching permits you to make parallel histories inside one mission. It is a key aspect to simple collaboration, and an excellent understanding of branching and merging is a prerequisite for successfully utilizing distant companies similar to Gitlab and GitHub.


After you’re feeling an skilled on Git, within the considerably longer and final video within the collection, we lastly clarify how we will use Gitlab and different distant git companies to collaborate on git initiatives. Extra particularly, you’re going to get an Introduction to totally different internet hosting platforms, then get the next


You may get Git on your system from git-scm. The lectures on this course are solely meant as an introductory presentation, not as an exhaustive course. You’ll discover all related particulars within the Professional-Git e-book by Chanon and Straub. For particular questions you’ll 99% of the time discover solutions on StackExchange.


By the tip of this course, it is possible for you to to reply the next questions:

1. What’s git?

2. What’s distinction between git and GitHub and GitLab (for CI software additionally we will use)?

3. Every other model management instruments aside from git?

4. What’s distinction between svn and git?

5. What’s merge conflicts have you ever confronted ever in you expertise? for those who face the way you resolve?

6. What’s git stash?

7. What’s git HEAD?

8. What’s staging space in git?

9. What’s distinction between git fetch and pull and clone?

10. What’s distinction between git merge and rebase?

11. What’s .gitignore file? What’s the function of the file?

12. What’s git department? Have you ever labored on branches?

13. How to merge branches?

14. What’s cherry-pick in git?

15. How to create a git mission?

16. How to verify distinction in between two recordsdata?

17. How edit the dedicated message?

18. How to verify the previous few commits?

19. How to delete distant department and native department?

20. How to create native department?

21. What’s tag? What number of sorts in tag? How we’ll create tags?

22. How to roll again dedicated code.


Within the bonus part, which is about utilizing the GPU to considerably velocity up all types of numerical issues. You’ll Typical knowledge dictates that for quick numeric you want to be a C/C++ wizz. It seems you could get fairly far with solely python. On this video, I clarify how you need to use Cupy along with Numba to carry out calculations on NVIDIA GPU’s. Manufacturing high quality just isn’t the perfect, however I hope it’s possible you’ll discover it helpful.

Introduction: GPU programming in python, why?

Cupy intro

Cupy demonstration in Google Colab

Cupy abstract

Numba.cuda and kernels intro

Grids, blocks and threads

Matrix multiplication kernel

Tiled matrix multiplication kernel and shared reminiscence

Numba.cuda demonstration in Google colab

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