I am currently trying to follow a tutorial as I just started to learn Machine Learning.
I am trying to predict stock prices. Here is my code:

`

import pandas as pd
import matplotlib.pyplot as plt
import yfinance as web
import numpy as np

from sklearn.preprocessing import MinMaxScaler
from tensorflow.python.keras.models import Sequential
from tensorflow.python.keras.layers import Dense, Dropout
from tensorflow.python.keras.layers.recurrent import LSTM

company = 'TSLA'

start='2012-01-01'
end='2024-03-01'

data = web.download(company, start=start, end=end)

scaler = MinMaxScaler(feature_range=(0,1))
scaled_data = scaler.fit_transform(data['Close'].values.reshape(-1,1))

prediction_days = 60

x_train = []
y_train = []

for x in range(prediction_days, len(scaled_data)):
    x_train.append(scaled_data[x-prediction_days:x, 0])
    y_train.append(scaled_data[x, 0])

model = Sequential()

model.add(LSTM(units = 50, return_sequences=True, input_shape=(x_train.shape[1], 1)))
model.add(Dropout(0.2))
model.add(LSTM(units = 50, return_sequences=True))
model.add(Dropout(0.2))
model.add(LSTM(units = 50))
model.add(Dropout(0.2))

`

I excepted it to input out nothing, however I got this error:
but it says as an error,
‘

Traceback (most recent call last):
File
"c:UsersUser1OneDriveDocumentsDesktoppythonprojectsmachinestock_price_predictor.py", 
line 32, in <module>
model.add(LSTM(units = 50, return_sequences=True, input_shape=(x_train.shape[1], 1)))
                                                               ^^^^^^^^^^^^^
AttributeError: 'list' object has no attribute 'shape'

‘

Do any of you know how to solve this? I tried converting it into np.array but nothing worked.