Відео

thanks a ton

Where did u get the N

Thank you. This was a really helpful video.

nice didnt work "Error in configuration process, project files may be invalid." i see you responding to all msgs just not these ones so no help at all

model.compile(loss=['binary_crossentropy', 'mae'], optimizer='adam', metrics=['accuracy', 'mae']) In this line you add additionaly mae to metrics in your github repository. when I try with following line in google colab It does not work, showing error. But in your above video, It works propperly, what is the reason for that. Can you explain? model.compile(loss=['binary_crossentropy', 'mae'], optimizer='adam', metrics=['accuracy'])

Hi , while fitting the model, we use X and y where y = ['Survived'] . Now X has has no NaN values but Y does . So it throws an error. Since y is our target varable , is it appropriate to fill the missing values with mode?

Thank you for the help!

Hey nice Video!! But I have one question to fill missing values for Item weight with mean values why didnt you simply use "median = df[''Item_Visibility'].median() df['Item_Weight'].fillna(median, inplace=True)" What is the point of the big code? Starting from Line 11

can somebody please explain from where we get 1.5 in the IQR method? why exactly 1.5?

i got error in configuration process, project files may be invalid

is it possible to run the code in google colab

Can we use our own data for response, means I ask question the response should hit the database and it should send the response.

Getting this error while training the model - assertion failed: [You are passing a RNN mask that does not correspond to right-padded sequences, while using cuDNN, which is not supported. With cuDNN, RNN masks can only be used for right-padding, e.g. `[[True, True, False, False]]` would be a valid mask, but any mask that isn\'t just contiguous `True`\'s on the left and contiguous `False`\'s on the right would be invalid. You can pass `use_cudnn=False` to your RNN layer to stop using cuDNN (this may be slower).] [[{{node functional_1_1/lstm_1/Assert/Assert}}]] [Op:__inference_one_step_on_iterator_423791] I have not changed anything in the code. Running your code only. Please suggest what to do?

I replicated it, but is performing poorly how can we improve the performance, will using random forest be useful? please tell some others ways also to improve performance

Keeping UA-cam channel and directly writing code is not matters, FIRST learn how to explain question to viewers after you start coding Bad explanation cheating....

Please could you explain, how can we train on our own dataset, I watched most of the videos on Fine-tuning llm using unsloth, almost everyone just using template to of huggingface dataset load , no one explain about how can create your own instruct - chat dataset and use that dataset, for example I have questions answers pairs each next question follow ups to previous answer, I want to train in context

please send source code link

Can you provide a step by step roadmap for learning all this

bro please make more videos on data structures and try to make videos of problem solving of data structures in hackerrank

Training data contains 1 samples, which is not sufficient to split it into a validation and training set as specified by `validation_split=0.1`. Either provide more data, or a different value for the `validation_split` argument. I am facing this error while training of model, how can i solve this? and i am using kaggle colaboratory

Worked perfectly 🎉 thanks

Thanks for sharing the solution!!

Why n//=2 I

The important thing to keep in mind is that If we approach this problem using normal map = dict(), it will KeyError for arr[i + 1] (because it may not be there in the map), However, if we use Counter(arr) to create the dictionary, then it will not give us KeyError (It will simply return 0 for any key not in the map).

Question was not written accurately. They first tell us to find SUB-ARRAY, then in the Test Case, they expect us to find SUB-SEQUENCE.

how do you make tough questions look so simple. Great job thala!

Upar ke modules execute ni hore ????kya kare?

why we need to convert entire string into lowercase

Hi I am getting issue class:an error occurred:name "model" is not defined

Thank you so much!!!. A question: in what type of distributions can the box plot be used? For example, if the data follows a uniform distribution, does it make sense to find outliers? What do you recommend me?

Amazing tutorial. Bro, you made my day. Lots of love from Pakistan.

can you please make a roadmap on Machine learning + resources

i am not getting the program to be run correctly maxsum=-99 for i in range(4): for j in range(4): top=sum(arr[i][j:j+3]) mid=arr[i+1][j+1] bot=sum(arr[i+2][j:j+3]) hourglass=top+mid+bot maxsum= max(hourglass, maxsum) return maxsum this is the code

What when position is 0 ?

I have a scenario of extracting most relatable ( having more words matching ) audios using an input audio. What's the best way to approach this problem ? If it is embeddings then how I'll go about it and if not, then tell me which one would be better.

As far as I know, initially we use smaller learning rate because at the start of the training our model usually takes larger steps to reach the minima, but as it progresses it becomes slow so if we are dealing with a large dataset we can simply use higher batch size like 8192 etc and by using warming up the learning rate (which will gradually increase the learning rate during training) so that our model can converge not only more faster but will yield more accurate results (generalization) as a lower batch sizes of 32, 64 usually yields.

Can you please send the code

Thanks for the video. I am currently working on EfficientNet and Topological data analysis. I have to extract features from the TDA and then from EfficientNet and then combine it and run it on SVM. Can it work there too?? Thanks again

Can you make separate course for time series.

such a great video! i want ask what if i want to enchance a bunch of image in 1 directory

Its so nice and very helpful. Thank you so much ❤

Second question, at the end you are testing your model with images that comes from X, and X has been used to train the model so aren't you testing the model on images that it already saw?

Hello! Thank you for the video. I was just wondering why didn't we look at the accuracy for the age?

Wow sir hats of to your logics

Thank you so much for this. I have been trying to install opencv with cuda for a few days now and there was always some new error that I could not resolve. This is the first tutorial that worked without any issues. Thank you so much!!

Hey Hackers, From minute 26-28, the video is screen was frozen during recording while the audio is available, you can see the code in the notebook after that. Thanks for your Patience!!!

what is this yan(n) here?

bro thanks a lot but initially i got so many errors that it had taken my 2 days but i used chatgpt, google, youtube to resolve all that issues and At the End i got it.

How can i deploy a virus in my local callcenter ?