Python NumPy Tutorial | NumPy Array | Python Tutorial For Beginners | Python Training | Edureka

///Python NumPy Tutorial | NumPy Array | Python Tutorial For Beginners | Python Training | Edureka

Python NumPy Tutorial | NumPy Array | Python Tutorial For Beginners | Python Training | Edureka

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( Python Training : )
This Edureka Python Numpy tutorial (Python Tutorial Blog: explains what exactly is Numpy and how it is better than Lists. It also explains various Numpy operations with examples.
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This tutorial helps you to learn following topics:

1. What is Numpy?
2. Numpy v/s Lists
3. Numpy Operations
4. Numpy Special Functions

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By |2019-08-21T22:14:07+00:00August 21st, 2019|Python Video Tutorials|44 Comments

44 Comments

  1. edureka! August 21, 2019 at 10:14 pm - Reply

    Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For Edureka Python Course curriculum, Visit our Website: http://bit.ly/2FBUtO7

  2. Varsha Vatsyayan August 21, 2019 at 10:14 pm - Reply

    Very helpful! thank you

  3. SasikiranKakara Prince August 21, 2019 at 10:14 pm - Reply

    impressive sir awesome!!

  4. mudit goyal August 21, 2019 at 10:14 pm - Reply

    fast, effective and very informative session.

  5. Hitesh Godse August 21, 2019 at 10:14 pm - Reply

    Thanks! Very informative

  6. pratibha raj August 21, 2019 at 10:14 pm - Reply

    Sir tell about linespace

  7. Ali Asghar August 21, 2019 at 10:14 pm - Reply

    you r great sir!

  8. Shubham Fulzele August 21, 2019 at 10:14 pm - Reply

    Thanks a lot…

  9. Varun sharma August 21, 2019 at 10:14 pm - Reply

    Is there any difference between np.ravel() and np.flatten()

  10. Ratna Gudapati August 21, 2019 at 10:14 pm - Reply

    why numpy are faster than list?

  11. Vallamkonda Neelima August 21, 2019 at 10:14 pm - Reply

    thank you sir

  12. Sambita Chakraborty August 21, 2019 at 10:14 pm - Reply

    Informative and very nicely explained.

  13. Nilothpal Bhattacharya August 21, 2019 at 10:14 pm - Reply

    I have a question around the matrix multiplication approach …is that correct?

  14. Jitmanew Tyagi August 21, 2019 at 10:14 pm - Reply

    13:39 thank me later

  15. Devanshi Singh August 21, 2019 at 10:14 pm - Reply

    thanks for the help

  16. Ajay Agrawal August 21, 2019 at 10:14 pm - Reply

    Ultimately explained video I have ever seen. I have noted down each and every point that you have told. Thankyou so much.

  17. Raj Agrawal August 21, 2019 at 10:14 pm - Reply

    Excellent session.. thanks for sharing it.

  18. Ananya Rai August 21, 2019 at 10:14 pm - Reply

    Thank u sir!

  19. Adnan Lokhandwala August 21, 2019 at 10:14 pm - Reply

    Thank you, that was very helpful πŸ™‚

  20. Logic stuff August 21, 2019 at 10:14 pm - Reply

    thanx it's very comfortable to learn

  21. jason myers August 21, 2019 at 10:14 pm - Reply

    why would you need the time.time()-start please help

  22. Abdo_Muaadh Alsapri August 21, 2019 at 10:14 pm - Reply

    thanks allot its very clear thank and thanks again and again ………………………………

  23. Sanjeet Kumar August 21, 2019 at 10:14 pm - Reply

    very informative session..

  24. Sabyasachi Mukhopadhyay August 21, 2019 at 10:14 pm - Reply

    Excellent Session!

  25. ruhail ahmad August 21, 2019 at 10:14 pm - Reply

    "c = np.array([(9,10,11,12),(13,14,15)])
    print(c)"
    what will above code print?

  26. aman maheshwari August 21, 2019 at 10:14 pm - Reply

    amazing session…great work

  27. aman maheshwari August 21, 2019 at 10:14 pm - Reply

    when we get the datatype as int64

  28. C Moulali August 21, 2019 at 10:14 pm - Reply

    Very good video 😍😍😍😍😍😍😘😘

  29. Debabrata Tah August 21, 2019 at 10:14 pm - Reply

    why you do " time.time()-start ". i cant understand this. pls explain

  30. lavanya devarasetty August 21, 2019 at 10:14 pm - Reply

    What is pycharm.and how to install ( proper website name to install pycharm).
    instead of pycharam can we do it in .anaconda and in Jupiter notebook

  31. Prakhar Srivastava August 21, 2019 at 10:14 pm - Reply

    How to get this Numpy 2D Array as input from the user ?

  32. Rajat Parab August 21, 2019 at 10:14 pm - Reply

    Excellent content and explanation
    If possible pls post a series or more videos related to python
    Like the comment if you want it as well

  33. Anh Minh TrαΊ§n August 21, 2019 at 10:14 pm - Reply

    Awesome tutorial. Very clear, short and concise. Thank you =))

  34. Pmrsuresh August 21, 2019 at 10:14 pm - Reply

    or else we have another class for Numpy?

  35. Pmrsuresh August 21, 2019 at 10:14 pm - Reply

    Is it completed the Numpy class?

  36. Beautiful World August 21, 2019 at 10:14 pm - Reply

    You are amazing! Thanks…

  37. subhranil banerjee August 21, 2019 at 10:14 pm - Reply

    Amazing session πŸ™‚

  38. Srikanth Seshadri August 21, 2019 at 10:14 pm - Reply

    Very informative

  39. Ajit Kumar August 21, 2019 at 10:14 pm - Reply

    In numpy and list speed comparison part of the video. I think the list code should be modified as
    result = [x+y for x, y in zip(L1,L2)]
    Then only it will be give equal result of result = A1 + A2

  40. Narendra Zone August 21, 2019 at 10:14 pm - Reply

    Excellent explanation. Very useful video.

  41. SSDK ONELESS August 21, 2019 at 10:14 pm - Reply

    i think there is a little mistake in computing the sum at 11:02 the list sum comprehension should be [x+y for x,y in zip(L1, L2)] and not [(x,y) for x,y in zip(L1, L2)] A great lecture sir thanks . if u can answer i have just a small query .
    is pyplot a methd in matpotlib , if yes then when i used from matplotlib import * and used pyplot.plot() then it raise a error as no attribue found .can u help me getting this on my mind.@edureka!

  42. Titus D'souza August 21, 2019 at 10:14 pm - Reply

    Very Good!

  43. Mas Zadmehr August 21, 2019 at 10:14 pm - Reply

    Right to the point, very concise and all the common operations covered. Thank you.

  44. Black Ghost August 21, 2019 at 10:14 pm - Reply

    Awesome. Great presentation

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