Who want to clap for this man👏👏

Hello Krish, I am obliged to take time and express my gratitude towards your efforts and teaching method. I am watching your tutorials since yesterday, and I just so happy to learn and actually understand everything. I am looking forward to follow the playlist, and excited to learn. Thanks man, you deserve our respect and the money as well, I will be joining your membership. I will request all the people who are reading my comment to consider joining the membership to help him grow❣

Q1-If I pick up 4,5 from 2nd row And 6,8 from third row than In. is Arr[1: , 2:4] Q2-Pick up 3,4,5 from 2nd row than In. is Arr[1:2,1:4] Thank you so much sir.

Thank you soo much Krish. I am recommending your channel to all my friends. I really like your genuine teaching passion. I learn a lot from all your videos. Thanks for being a mentor.

Absolutely great content being put here by this man. I wish there were more teachers like him across different domains. What a stupendous job he is doing here.

For the subarray 4, 5, 6, 8 code is: arr[1: , 2: 4] For the subarray 3, 4, 5 code is: arr[1, 1: 4]. I started your session, sir, really your contents are truly valuable. Thanks for making this all happen. I wanna learn as best as possible about the concept of Machine Learning. Really glad that I found your channel at the time when I was in its complete need. Thank you soo much, sir

Bro! You're helping us all a lot! Proud of you! An Indian teaching everything in depth. Thanks so so much. Keep up the good work. Looking forward to pandas tutorial too. 🤘🏻🤘🏻🤘🏻

I never thought understanding the prerequisite of machine learning is that much easy and Krish sir you make it alot easier.

Hi Krish, Python is made so simple to learn from you. Always had difficulty in understanding and remembering from other tutors. Never felt it so easy and enjoyable to learn. Thank you for your efforts.

I started watching this playlist today after knowing the learning path from your yesterday's video. thanks a lot

Honestly glad to have come across your channel and it brings in humungous value to the folks trying to learn. You are truly the best. You make commendable efforts and as a part of the learning community, I hold enormous respect for your contribution in helping us. (y)

This is the first video of your channel that i got recommended and man i loved it . Thanks for sharing.

Goat of Python bro, learned 3 months work in 3 lectures.

arr[1:3,2:4] = array([[4, 5], [6, 8]]) Thank you Krish! I am following your path to become a Data scientist

Thank you Krish Naik for teaching us by this much of patience. You have cleared so many of my doubts.

EAGERLY EXPECTING Scikit learn and PLOTLY tutorials. No one has taught about Plotly... If you make this it would be great....

Following are taught in video: -Array definition - Numpy library import - Array Shape and Reshape - Array indexing - Array Range - Array linspace - Array copy and broadcasting - some functions in Array like np.ones, np.random.rand (random distribution), np.random.randn (normal distribution), np.random.randint etc.

His explanation is clear and everything is practical.

print(arr[1:,2:4]) print(arr[1:2,1:4])

For accessing 4,5,6,8 answer is arr[1: , 2:4] and for accessing 3,4,5 answer will be arr[1:2,1:4]

Highly insightful

Excited to watch more tutorials on deployment

great explanation!!! if I cover all these concepts I will be data scientist within couple of months: Absolute best explanation..

Just 3 videos into and you made it really interesting ❤️❤️🙏🙏🙏

Thanks for the videos. One change : Here, even if the elements are of not same data type, arrays can be created. So, they need not be of same data type. import numpy as np my_lst1=[1,2,3,'sdfs',5] my_lst2=[2,3,4,5,6] my_lst3=[9,7,'wow',8,9] arr=np.array([my_lst1,my_lst2,my_lst3]) print(arr)

thank you again....i gonna finish your amazing course in a week

*Numpy *Array 1.Creating One Dimensional array. 2.Creating Two Dimensional array. 3.Shape, reshape and indexing(slicing) done in two dimensional. 4.In-built function present in numpy- arange, linspace, ones, random.(and more) 5.Concept of copy and Exploratory data analysis Please share the list built-in functions of numpy. Thanks

Sir Thank you so much your playlist is very used full and it was very fast unsersting.

wow Sir. Love all your videos. Thank you !!

Hi Krish, great effort. But i request you to improve the audio quality. Audio quality is not so good to follow the recording. thank you.

Hi..In[105] -( val=2)..in this case we take "val" to do the operations like...arr*val, arr>val,.......correct me if i am wrong..Thank you Krish for your valuable teaching

this is one of the best playlist for learning python for data science, can you please tell me how can I practice without anaconda environment? As my PC does not support the environment.

your explanation is very good

I understand this chapter of numpy in 3 days there are lot to learn in 26 minutes.

First of all thank u so much for amazing tutorials on python. I have a question. When I do this, my_lst=[1,2,3,4] arr=np.array([my_lst]) arr The output comes as array([[1,2,34]]) Is it two dimensional then?

Very nice explanation .Thanks

I have a request to make : if you could provide a mind map of the things that we are learning in numpy, pandas, matplotlib and other python libraries that we are going to learn that would be really helpful.....getting to know all the things that we have to learn will be better for better understanding and remembering also. looking forward to your reply.

Here are the functions mentioned in the video with examples: * Creating arrays: * `np.array()`: This function is used to create arrays from various data types like lists, tuples, etc. For example, `np.array([1, 2, 3, 4, 5])` creates a one-dimensional array with elements 1, 2, 3, 4, and 5. * `np.zeros()`: This function creates an array filled with zeros. For example, `np.zeros((3, 4))` creates a two-dimensional array with 3 rows and 4 columns, all filled with zeros. * `np.ones()`: This function creates an array filled with ones. For example, `np.ones((2, 2))` creates a two-dimensional array with 2 rows and 2 columns, all filled with ones. * `np.random.rand()`: This function creates an array filled with random floats between 0 and 1. For example, `np.random.rand(2, 3)` creates a two-dimensional array with 2 rows and 3 columns, filled with random floats between 0 and 1. * `np.random.randn()`: This function creates an array filled with random samples from the standard normal distribution. For example, `np.random.randn(3, 3)` creates a two-dimensional array with 3 rows and 3 columns, filled with random samples from the standard normal distribution. * Indexing and slicing: * `[]`: This operator is used to access elements of an array. For example, `arr[0]` accesses the first element of the array `arr`. * `[:, :]`: This is used to access all elements of an array. For example, `arr[:, :]` accesses all elements of the array `arr`. * `[start:stop:step]`: This is used to slice an array. For example, `arr[1:4:2]` selects elements from index 1 to index 4 (excluding index 4) with a step of 2. * Mathematical operations: * `+`, `-`, `*`, `/`: These operators are used to perform basic arithmetic operations on arrays element-wise. For example, `arr1 + arr2` adds the corresponding elements of arrays `arr1` and `arr2`. * `x * arr`: This multiplies each element of the array `arr` by the scalar `x`. * `arr.shape`: This attribute returns the shape of the array as a tuple of integers. For example, `arr.shape` might return `(3, 4)`, indicating that the array has 3 rows and 4 columns. * Reshaping: * `np.reshape()`: This function is used to reshape an array into a new shape. For example, `np.reshape(arr, (2, 6))` reshapes the array `arr` into a two-dimensional array with 2 rows and 6 columns. * Other functions: * `np.dot()`: This function is used to perform dot product or matrix multiplication between arrays. * `np.sum()`: This function is used to calculate the sum of all elements in an array. * `np.mean()`: This function is used to calculate the mean of all elements in an array. These are just a few of the many functions available in NumPy. I hope this helps! -courtesy:GeminiAI

done...heading to video number 8 :)

Awesome

What is the difference between arrays with the following shapes: (x,) and (x,1) Aren't both the same, i.e. an 1D array?

How do I query if column 2 is grater than column 1 in three dimensional arry? [(2,3,4),(1,4,6)] check if 3>2 & 4>1

Are you also preparing for UPSC at the same time? :)

Assignment - array[1:,2:4] array[1:2,1:4]

array of 45 68 ----- arr[1:,2:4] array of 345 ----- arr[1,1:4]

hi Krish, What's the difference between random.rand and random.random_sample ? btw, these lectures are super helpful!! Thank you so much for this

Hi Krish, I want to enrol in the course but I am not able to open the google form. Could you please help me out. Thanks Priyadarshi

while creating a dimensional array, why does the shape indicates (5,0) and why not (1,5)?

hello sir i am getting an error " module 'numpy' has no attribute 'arrange'". how this is to be resolved??

Done and Implemented !!

Thank you

Hi, for assignment @14:23... 1. arr[1:,2:4] & 2. arr[1,1:4]

arr[1:2, 1:4] output: array([[3, 4, 5]])

1. arr[1:, 2:4] 2. arr[1, 1:4] Is this answer right for your question?

Sir i have exam tomorrow, r these numpy functions sufficient for my exam???

Thanks Krish

time: 14:30 assigment asn: array[1:,2:4]

#slice operation to print only [3,4,5] in second row arr[1:2,1:4]

for indexing... arr[1:,2:4] arr[1:2,1:4]

arr[1:3, 2:4] array([[4, 5], [6, 8]])

i havent studied statistics can i complete python playlist then move to statistics or have to compalsary study statistics first ?

Thanks a lot Sir ,

arr1[1:,2:4] for [4,5,6,8] and arr1[1:2,1:4] for [3,4,5]

Hi Krish, if the first list has 3 elements, 2nd has 4 elements and 3rd has 5 elements then still NumPy can create a multidimensional array?

Thanks krish

Hi,please make a video on pandas,scipy. Thanks

Answer to print 1.) 3,4,5 @14:20 arr1[1:2,1:4 ] 2.) 4,5 and 6,8 arr1[1: , 2:4]

done!

Hello sir. Can you please create a video where you can guide us through the index and order on how to watch your videos ? I am facing a lot of problems in this regard. Thanks!👍

I have a confusion.. when we execute copy() function and print arr and arr1 then why is the space difference between the two array?

Is there any WhatsApp group or website or something similar where we can ask doubt regarding Machine Learning? Please tell me

solution for the excercise - arr[1:,2:4]

18.07 when we print "arr" the output array is comma seperated but when we print "arr1" output is space seperated.. why? when we use linspace the array is of shape 10 rows and 5 columns .. why? and why not 25 rows and 2 column or other?

Sir in this vedio u r voice was little bit bistrubanceis their and remaining all vedios r good

Hello, How can We select 1st and 3rd row and 2nd and 4th column. Is it possible using numpy?

14:25 [1:,2:4] [1:,1:4]

But when I was trying to insert different data type into an array , it is accepting

thanks

I am not able select multiple cells using shift+Down arrow or shift+J. Help will be appreciated.

New threads comes in :5: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray. arr=np.array([lst1,lst2,lst3]) this want work anymore

Bro I find your tutorials are so good and useful. I have a question where to start...?. There are lot of video playlists like stats,Ml,python...Please suggest me to learn data science as a beginner ,first i have to go through stats or Machine learning...please suggest bro,

Sir can you please do project on mechanical engineering domain??

Sir how to access private video

sir can u plz help me..mai Pychm use kr rhe hu bt use me numpy import error show kr rha..mai google kiya kuch nhi mila information ki kaise thik kru..bs yahi bol rhe h problem aati h so plz help

Hii Krish I am confused in .copy() concept

hello,sir,,is this concept of numpy enough to go through machine learning

Sir, I want to enroll to this course. Please let me know how I can join this..

Krish if [0:2,:] means it needs to retrieve all three rows right? But in this tutorial we are getting only first two rows as output . how? shall you kindly explain?

arr = [1, 2, 3, 4, 5, 6, 7, 8, 9] arr1 = arr.copy() arr1[3:] = 67 print(arr1) for this code i'm getting errory , i replaced it with [67] the out put is only [1,2,3,67] how can i get all the remaining values as 67

can we copy or replace number with srting vaue

Arr[1:, 2:4] and arr[1,1:4]

awesome

Hey we're is the course curriculum details which I saw below one of ur videos. Also experience error in enrolling in ur course.

print(ar[1:,2:4]) print(ar[1:2,1:4])

sir what is the difference between range () and arange()

Completed on 30/6/2024

Completed 28 June 2023

audio quality is bad sir, could you please fix it for upcoming videos, thank you!

arr[1:,2:4] = array([[4, 5], [6, 8]]) arr[1:2,1:4] = array([[3, 4, 5]])

arr[1:4,2:4] ,arr[1:2,1:4]