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

is this multivariate time series or univariate

He's BACK!!!

Great Explanation !!

Very good. You would make an excellent teacher. Get a PhD in USA and join teaching at a University.

Has anyones got output correct? Mine is showing error after input

Better Explanation than 2 hr lecture

What If we have Week instead of date column.... Can I use parse_date= 'Week'

why the predictions column does not display in my code 😭😭

Hi, I am not finding the dataset used here. Please guide me where to find it.

pls, can you send me the source code to my Gmail because i can't access GitHub. I need it for my final year project.

Pls share the data set thanx

thank you so much !! You explained so well, then it's very easy to understand!!

what to do if the probability is high?

Hi, but what if we dont have data for all the months like there is for 10 months but 2 months the sales wasn't done for the product so it wasnt added? Like if I have monthly wise data instead of daily what can I do? Like I have date like jan 2019 and so. If I convert to datetime in python it shows 01-01-2019 for jan and then all months start with 01 for the following year.

Hi but when I try installing fbprophet in jupyter it doesnt install and give me this error Failed to build fbprophet pystan IOPub data rate exceeded. The Jupyter server will temporarily stop sending output to the client in order to avoid crashing it. To change this limit, set the config variable `--ServerApp.iopub_data_rate_limit`. Current values: ServerApp.iopub_data_rate_limit=1000000.0 (bytes/sec) ServerApp.rate_limit_window=3.0 (secs)

I'm looking all of the videos on KZbin related to time series to understand all model's but couldn't understand well, when I had found this gem nd got it all..he creates ppt like subconsciously saves in mind...hatts up bro❤

Good job Boy!!! Well explained

Hi, i have a question. In the video at 8:25, you said it slightly overfitting. Can you help me what to do to resolve the overfitting problem? I have the same issue like in the video? I'm new to this, hope you help me. Thanks!

Thanks 😊

this was so helpful, thank you so much!

AttributeError: module 'gradio' has no attribute 'inputs'

thanks for great video. I have a question. I applied this code to my data auto arima. The only difference is that I have seasonality=12 months. So how should it be the code for manual arima?

Hello sir. I cant seem to find the predicted charges after. Any clues on where I could find them

good vid.

Can this be done in vs code instead of pycharm?

Exactly what I needed. Thanks❤

If I become expert ai ml engg, one day in future I will give credit to you - for your line 🔥💫 Programming is replaceable, but maths and algorithms basics will remain there I was worried, do I am wasting my time learning maths, when I know programming

Wonderful Bro!