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Hi!, thanks a lot for your videos, they're quite helpful! Do you have any other textbook recommendations for learning timeseries forecasting? The ones you've mentioned are practical/more python centric, I'm interested in mathematical/theoretical textbooks. Thanks!

When explaining Time Series modeling on Python, anyone would assume and directly say this pd.read_csv standard function. But he takes time in explaining the attributes of this function even for a basic beginner to understand which is something worthy. :)

Hi Nachiketa, I have a question. In ARIMA model the integrated part allows us to difference the time series to get a constant mean. This will remove stationarity only in cases where the series violates only the non-constant mean property. But if there is a series which has volatility and seasonality then what can be done in such a scenario?

Really nice explanation! Wish you were my college prof

Hi, i ran the ARIMA model . everything went fine, except the graph visualization was erratic. please comment . it will be great help

Could you please explain the significance of dynamic being set to False inside the model.predict function

bro i learned this for 1 semester and you just explained it in 10 minutes....and i understand it. how

💥💥

the 2nd and 3rd examples that you show for white noise seems seasonal........is this stationary and can we directly predict using this data

can you make a video without using inbuilt function

why there should be no seasonality

bhai hindi m bataya kr yr

Hi I am working on a project where i have to predict the registration percentage drop. I am retrieving the data from an API. But the accuracy is too low, the predicted mean graph is extremely inaccurate in comparison to the actual graph, could you maybe check and help me with the code?

The current menues of aws does not match the ones you use. There are alot more spaces to fill out now and I couldn't get it to work following your instructions :(

really well said

use a list of points and use an o(nlogn)NN search.. a cross validation between points where each point is a model

Sir please can u help me in this project 😭🙏🏻 I have to make this type of project for my school My project is of making lock system using Arduino and a keypad It will work like there will be a locker and we have to type password on keypad if the password will be correct in first time then the locker will be open but if it will be wrong twice simultaneously a sms will go to all the family members can I make it using brynk app????

Great content sir If you have provided the resources in Github that will help so many

thank you

he is smartass😀

hello my friend. i am planning to use resnet50 for my project. basically the project is about birads classification. i have dataset which has around 3000 images and 3 classes (birads2, birads4, birads5). i want this model to classify the mammography pictures as birads classification. i tried to fine tune this model but it didn't really work. do you have any suggestions or hints for me to tune this model for such a detailed and complicated birads classification?

Can we host streamlit applications ?

i am not able to read csv file , what is the reason

U have given a very good intuition

Amazing videos! Thank you!

Hi, THanks a lot for you fantastic teaching. If I want to use one month as input and predict the next 12 month how can I change the code. As I understand you feed 12 months as input and the prediction is for one month

bhai apne itna accha knowledge kaha se liya ??... thanks for passing it brother GOD bless you

2 months study and one can land job in India 😮😂

nice explanation

Is it good to take AIML engineering or CSE

If we divide again from train dataset as for suppose 80:20(train and val), then val is also a part of train, and its an unseen data, then the total trained images are reduced when we compared it to 80:20(train and test) without val accuracy. can you justify this?

Amazing presentation. Learned a lot in short time

Hi, thanks for your nice talk. As I understand ARIMA is ARMA model when D=0, the the parameter D is to make it stationary. But ARMA can be nonstationary. So instead of using ARAM we can use ARIMA and examine different D in order to make it stationary. Therefore, there is no point in using the ARAM model. Would you please let me know if I am right or wrong?

"You exceeded your current quota, please check your plan and billing details",it shows like what's the solution?

This is like gridsearchcv or randomizedsearchcv😮

💎🛐

Great video....but I worked on this and I am getting template not found error....any suggestions on that😢

Great Explanation brother!! Keep it going...

Can i use this code with 3 year data's

when I run this code blog, I encounter below error. how can I fix it? epochs=10 history = resnet_model.fit( train_ds, validation_data=val_ds, epochs=epochs ) ------------------------------------------------------------------------------------------------------------------------------ Epoch 1/10 --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-40-965fc73b902c> in <cell line: 3>() 1 epochs=10 2 ----> 3 history = resnet_model.fit( 4 train_ds, 5 validation_data=val_ds, 1 frames /usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py in tf__train_function(iterator) 13 try: 14 do_return = True ---> 15 retval_ = ag__.converted_call(ag__.ld(step_function), (ag__.ld(self), ag__.ld(iterator)), None, fscope) 16 except: 17 do_return = False ValueError: in user code: File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1401, in train_function * return step_function(self, iterator) File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1384, in step_function ** outputs = model.distribute_strategy.run(run_step, args=(data,)) File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1373, in run_step ** outputs = model.train_step(data) File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1151, in train_step loss = self.compute_loss(x, y, y_pred, sample_weight) File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1209, in compute_loss return self.compiled_loss( File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/compile_utils.py", line 277, in __call__ loss_value = loss_obj(y_t, y_p, sample_weight=sw) File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 143, in __call__ losses = call_fn(y_true, y_pred) File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 270, in call ** return ag_fn(y_true, y_pred, **self._fn_kwargs) File "/usr/local/lib/python3.10/dist-packages/keras/src/losses.py", line 2221, in categorical_crossentropy return backend.categorical_crossentropy( File "/usr/local/lib/python3.10/dist-packages/keras/src/backend.py", line 5573, in categorical_crossentropy target.shape.assert_is_compatible_with(output.shape) ValueError: Shapes (None, 1) and (None, 5) are incompatible

bhaiya please tell how much do you earn from this computer vision engineer job??

Love itt... Thanks broo for helping us

Upload this project tutorial step by step

Best explanation on how to infer from a PACF plot. Amazing.

your video helped me a lot thank you

I have one doubt. [1,2,3] is used to predict [4]. Then [2,3,4] is used to predict [5]. In 2,3,4 shouldn't the 4 value be the actual instead of predicted? Why are we appending predicted value. Pls explain.

Hey I'm thinking of pursuing MTech in this field? Is it worth it considering today's scenario.kindly help me out

diletant

Bro please make a videos on your experience in doing masters in the US and current tech market

There is a big error in this algorithm, MinMaxScaler!!! Prices dont have min nor max my friend, you can not use this because it converts all the price occurences in ranges between 0 and 1, and it doesnt exist since prices can go to infinity