Seriously, side-by-side comparisons are the BEST !! As visual as it can get ! 🙏

Keith, I've taken a heavy interest in data science lately and your courses absolutely rock !!! Many thanks to you for teaching me these fundamentals in such an informative, easy-to-understand manner.

@George-te4ms

2 жыл бұрын

how is the progress?

This was a phenomenal overview of numpy. I feel confident that I can tackle more advanced topics now!

You Sir are an amazing teacher!! There are many software gurus in the world, but sadly few who can impart their knowledge as you do...

⭐️ Course Contents ⭐️ ⌨️ (01:15) What is NumPy ⌨️ (01:35) NumPy vs Lists (speed, functionality) ⌨️ (09:17) Applications of NumPy ⌨️ (11:08) The Basics (creating arrays, shape, size, data type) ⌨️ (16:08) Accessing/Changing Specific Elements, Rows, Columns, etc (slicing) ⌨️ (23:14) Initializing Different Arrays (1s, 0s, full, random, etc...) ⌨️ (31:34) Problem #1 (How do you initialize this array?) ⌨️ (33:42) Be careful when copying variables! ⌨️ (35:45) Basic Mathematics (arithmetic, trigonometry, etc.) ⌨️ (38:20) Linear Algebra ⌨️ (42:19) Statistics ⌨️ (43:57) Reorganizing Arrays (reshape, vstack, hstack) ⌨️ (47:29) Load data in from a file ⌨️ (50:20) Advanced Indexing and Boolean Masking ⌨️ (55:59) Problem #2 (How do you index these values?)

@yahyafati

3 жыл бұрын

Why?

@baylee1791

2 жыл бұрын

thanks bhai

@za012345678998765432

2 жыл бұрын

+

@sanketemala1118

Жыл бұрын

@@yahyafati u were dumb or something'

@alexroode2659

10 ай бұрын

@gokul8747 is the hero of this comment section

One of the finest Numpy tutorials. Keep up the great work guys!

This is the first tutorial that I actually finished. Thank you, Keith!

Well done. Quick ,short & straight to the point!

finally, done with the entire video, tbh, it took me 6 hours to get myself acquainted with the working of the NumPy library and the Jupyter notebook. Thank you for this awesome tutorial

1.25 speed is perfect, thanks for the video

@cybermanithan7514

3 жыл бұрын

thanks for tips

@marcustulliuscicero9512

3 жыл бұрын

I'm on 2.5

@ugos_bizarre_adventures_6866

2 жыл бұрын

Thx bro

@JaFupy

Жыл бұрын

Yup

@toke7342

Жыл бұрын

2x speed is better. Saves alot of time.

Thank you for great video, Keith Galli. I had some problem of understanding Numpy before. Thanks to your help, I have strong basic knowledge of Numpy :)

This is absolutely great content! Thank you so much for doing this!

Amazing! Thank you for the explanation dude. It is really helping me with a certification course that I’m taking now

This guy is smart and he makes this stuff really interesting !!! I like it !!!

great vid, thanks for leaving the little mistakes in there, helps me remember that I dont have to be perfect at this and remember every little thing

Absolute clarity and upto speed. Very comprehensive coverage.

@63khushalsolanki9

2 жыл бұрын

Thats the most english I have heard all day

@shdnas6695

2 жыл бұрын

@@63khushalsolanki9 lol

@agam1823

2 күн бұрын

@@63khushalsolanki9 real

love the content ! i have just started to learn numpy for my course and this certainly helped !! cheers , would be looking forward to your content!

Thanks you Keith , great video (also subscribed to your channel). Also thanks to FCC , love you for your service!

Nice mate! What a wonderful review from all the possible uses of Numpy. Thanks a lot!

Just finished it. It was really awesome! I like how you would look at your notes, so that we don't see you 😂. Thanks a lot for this tutorial Keith Galli. Not following any other tutorial on Numpy. Take love!

Much better than courses that I've paid good money for - Top Man Galli

This video improved my numpy information. So thanks everybody who contributed.

Thanks for the free class! I'm just learning programming :) I felt very motivated after I could make the array on Problem #1

@tonyohore288

Жыл бұрын

learning as well, would u like a study budy?

Thanks so much Keith, for the very educating tutorial. Quite explanatory

Thank you very much sir... the course is crystal clear... thank you

Even OpenCV a top choice among computer vision professionals uses numpy array to store the image data.... Basically if you know how to manipulate numpy array you can do fine / pixel level operations... really appreciate your video.

Thank you! The only thing was a little bit complicated to me is working with axis. None the less, great tutorial!

@user-tf1bs6yy3b

Жыл бұрын

رحؤنشضهكبءخؤذمء ء يددحمس

excellent tutorial. feeling comfortable with numpy now thanks to you :)

Thanks for your effort and the good stuff. Effective introductory! Thanks

Excellent pace and explanations -- thank you!

Super helpful tutorial. When you went back and used -1 indexes instead of exclusive 4's at 33:36 my world stopped imploding. Thank you.

@mechtorious

4 ай бұрын

Why tho?

Awesome Tutorial. Thank you very much, Keith !

for the part at 31:50 a = np.zeros((5,5), dtype='int8') a[:,0:5:4], a[0:5:4,:], a[2,2] = 1, 1, 9

ur tutorial IS AWESOME, plz do more man i also watched ur pandas too and it was as expectedly AWESOME tnx for the help man i appreciate it

Really well put together, thanks! :)

Really amazing introduction to numpy, it helps a lot Thank you man!

imp points: 5:38 contiguous memory 8:28 how are lists diff than Numpy 9:42 applications of numpy 26:17 full and full like

Thank You for clearing my concepts on NumPy library.

Best crash course on Numpy ! Thank you for your interesting videos

Thank you bro! This was an amazing tutorial!

Thank you Keith for this awesome tutorial!

Thanks bro you I have learnt a TON of stuff from your tutorials

The second exercise from last part we can do this as well: a[range(0,4),range(1,5)]

@bhavpreetsingh1842

3 жыл бұрын

shouldn't the two range functions be in square brackets so as to make them a list

@robsonsilvadasilva

3 жыл бұрын

@@bhavpreetsingh1842 Hello Bhavpreet. I think that is a good practice to use square brackets to read the function, but it`s not necessary. You can test and see that works :)

@akshat2778

3 жыл бұрын

Even i did the same way ✌️🤟

@lbars

3 жыл бұрын

Mine: np.hstack(a[0:4, 1:5])[0:19:5]

@brettnelson7518

3 жыл бұрын

a = Np.arrane([0, 4] [1,5]) is more efficient

This is a great tutorial, thanks!!

Here's how you watch these videos: Hover over your right arrow key and hit it when he's initializing or doing some boring stuff, and when something interesting happens, something you might wanna know, you stop, pay attention, maybe type something similar in your own jupyter notebook; continue. Don't watch it at 2x speed. It doesn't work... Reading docs is hard! So this video is really cool.

Great video! Just got confused on min 43:55, output 143 should be a sum, but rather we got an array.

Love. this. Truly great content and it was even nice to see the little faux pas because everyone has those!

Just completed this tutorial. Thanks a lot for the content. Peace Out!!

Thank you so much for this amazing video!

Good job, way to go. Salute from Brazil.

At the end, I indexed [2, 8, 14, 20] as np.delete(a[a%6 == 2], -1) to make use of the cool stair pattern

Excellent sir, very well explained !! Many thanks for uploading. 5 stars. ⭐⭐⭐⭐⭐

Thank you dude ! That was great !

Thank you very much for sharing the video. It was very helpful.

Very good job, it was very helpful to me, thank you!

Thank you for the useful content. The very quick start with numpy.

Thank you for the video, its help me a lot to understand the concept and the function

@easydatascience2508

Жыл бұрын

welcome to check my playlists also. I made most of the videos for Python and R. easy to follow.

Great tutorial completed full. Love from heart

Great Tutorial .. can u upload the pandas, scikit learn also.. So we will get the complete basic ml package

@rajdeepchakraborty7961

3 жыл бұрын

Also matplotlib

one of the best numpy tutorial ever

Thanks a lot for this video!! much appreciated really !

Great video . God bless you and you keep making such great videos

very good video for learning numpy every topic is covered very well.....

Thank you so much for this video. It helped a lot.

Thank You Very Much for teaching us this nicely

Fantastic Tutorial !!!! Loved It !!!

Thanks for this amazing course!!

thank you very much for your efforts,could you talk about pygame with pymunk on details?

Awesome Keith, thank you for this great video

Great video and awesome examples

thanks for making this video ! It's helpful !

completed. thanks man! u r amazing

I did the matrix exercise a bit differently: arr = np.ones((5, 5)) arr[1:-1, 1:-1] = np.zeros((3, 3)) arr[2, 2] = 9

@NinjaTxGaming

Жыл бұрын

Nice. I noticed, you can also just use 0 instead of np.zeros((3, 3))

Thanks a lot, man. You are amazing.

Watching this at 2x speed so I can learn Numpy in 29 minutes instead of 58 minutes.

@krrishkataria560

5 ай бұрын

i have installed video controller extension, i am watching at 2.5x

@biological-machine

4 ай бұрын

@@krrishkataria560Just don't watch the video and read the specific documentation. It will be even faster if you have skill.

Excellent video. Thank you so much.

Great video. LOVED IT!

Fantastic tutorial, thank you

At 31:50 - more compact form: output = np.ones((5, 5), dtype='int8') output[1:4:1, 1:4:1], output[2, 2] = 0, 9 print(output)

We can also solve the exercise at 33' using output = np.ones((5,5)) print(output) output[1:4,1:4]=0 print(output) output[2,2]=9 print(output)

@foofoo17

3 ай бұрын

I solved it in the same way as you :)

Great video. Thanks!

Really useful video! Been using Pandas for a couple years but learning Numpy is showing me why Pandas does the things it does.

That was PRETTY amazing. Thankyou. But the most interesting thing was that I was the exact 3k'th like because I liked and unliked the video several times to confirm it.

Thanks you for this amazing video , great explaination

Thanks for the tutorial! 👍

Thnx for these great lessons .😇

56:00 b=[ ] for i in range(1,31): b.append(i) c=np.array(b) c=c.reshape(6,5) print(c)

Really good information delivery.

Thank you so much for this video :) :)

Great stuff! My only suggestion is to edit out the pauses. Stuff more value into fewer minutes.

Thanks for the awesome video!

Hello Keith, I liked the video very much, your presentation is really very nice. I am a school teacher. Can I share your video with my students? So, they will also be benefitted. Here sharing means sharing after downloading. I am not going to do any modifications in the video for sure.

very very helpful. thank you!

Thank you. Very helpful.

Thank you for uploading this.

The first 11 minutes of the video have really useful info

thank you for this helpful tutorial!

what a descriptive video on numpy 👍👍👍

Awesome work dude. love from India

50:00 test = np.genfromtxt('sample.txt', delimiter=',', dtype = 'int32') This too works