Excellent video, thank you for sharing! I have a question, you're predicting Open, Close, Min, Max, Adj Close and Volume at the same time and get values for each one of these dimensions, that's what is called multivariate time series forecasting. But, when the LSTM is running, does it consider Close, Min, Max, Adj Close and Volume of the given period to predict the Open value? I mean are we predicting Open, Close, Min, Max, Adj Close and Volume INDEPENDENTLY or does the algorithm considers all the other dimensions to predict one of them?

thank you for providing such content

thank you for your video, it really explains every step and I'm glad I found your video!!🤍

Very good session.

I'm stoked! Thank you Rish 😃

a very intuitive video!

keep going thank you

Projects are unique but please add PREDICTIVE MODEL to give output on new sentence

maam please make a project on regression along with random forest , decison tree, EDA and feature engineering

thankyou maam These days companies are asking for project on time series analysis using arima and hypothesis testing. i really like your way of teaching , can you please make a project on this

thank you,please make a video on Semi-Supervised EfficientNet ,

Thankyou so much maam, was finding some easy to understand project but was not able to find any, thankyou for all the efforts, i wish you all the happiness of the world

Good tutorial thanks

Mam can you explain I bit about this bert , I went through ml , dl , now learning gen ai , in which I have covering transformers for now , and building projects for fine tuning and rag , where Bert falls in the category ?

Good. How do you extract the features? For analyzing which feature is the most important ones

I must commend you on your good work ! They are really informative. But please I have a challenge with VGG16 architecture. Is there a way to reach out to you privately on this

Thanks for your video 😊

mam , are you indian or foreigner

that's too good.. 🙌🙌

Thanks. Really informative. Need a video explaining the differences between different models and when to use where. Like in which scenarios NavieBayes will be useful and in which the SVM classifier will be useful

great work mam

Thank you so much for this video

and plz share a roadmap for gen ai mam

mam do you have linkedin

mam , any data science fyp idea , plz i am confused for my fyp

mam , plz explain , the difference between , fine tunning and rag , and implementing of rag, cause rag is much in demand now

❤

Thank you

Well, if you listen to certain MSM outlets, anytime a conservative says anything at all, especially if its true, someone will attack it as hate speech. I'm certain the comment I'm leaving here will be censored. Go figure, simple as that.

mam go for Llms they are also , interesting and can make many good projects on that , once again thanks for the valuable content

great thank you mam for the amazing explaination ! waiting for the feature engineering part

outstanding work, I learned so many things from your DL videos, can you please make a video on augmentation data with transfer learning using the image dataset you used in the lung cancer detection. thank you!

outstanding work, I learned so many things from your DL videos, can you please make a video on augmentation data with transfer learning using the image dataset you used in the lung cancer detection . thank you!

plz make a seperate videos for feature engineering and scaling

great work , plz , make a explaination video about svm ! and its implementation

great work , i am learning alot from your videos , plz make deep learning projects related to cv and nlp , and plz try to train and test from a raw dataset , will be thankful ! keep up the good work

thank you...

Please make a video on electrical transformer fault diagnosis using machine learning.

nice explanation, thanks

mam when are making video market segment analysis ml parts 2

Can you please share the Colab File download link

Thank you for the video, I trained it for more epochs and the result is --> in terms of accuracy it improves and after a few epochs the accuracy decreases and again it improves, it is imbalance but for only 1 class (healthy) so, does this kind of behaviour of model shows overfitting or some other problem ?

Can you please provide a link for this particular data set please

make one video with large end to project with deployment, hyperparameter tuning, ensemble learning, dimensionality reduction etc unique and advanced level also provide sourcecode(github)

from sklearn.linear_model import LinearRegression model = LinearRegression() model.fit(X_train, y_train) mam this part of code show error how can i solve this

Ma'am please share the source code also 🙏🙏🙏

Mam I need machine learning parts.can you create video parts 2

It shows an error when I select_datatype('object') and when I change it to int then my column size changes please help 🙏 At line 27

hi thanks for this, what is the best way to learn DL quickly for classification like this?

Mam I need market segment analysis project