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The prompt

Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Create an AI-based system in Python for predicting stock market movements. ### Input: Not applicable ### Output: #import libraries import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns #import data data = pd.read_csv('data.csv') #split data into train and test data X_train=data.iloc[:, 0] #Choosing the independent variable y_train=data.iloc[:, 1] #Choosing the dependent variable X_test=data.iloc[:, 0] #Choosing the independent variable y_test=data.iloc[:, 1] #Choosing the dependent variable #Build a deep learning model #import necessary libraries import tensorflow as tf from tensorflow.keras.layers import Dense from tensorflow.keras.models import Sequential #create a model and add layers model = Sequential() model.add(Dense(64, input_shape=(1,), activation='relu')) model.add(Dense(128, activation='relu')) model.add(Dense(64, activation='relu')) model.add(Dense(1)) #compile the model model.compile(optimizer='adam', loss='mse', metrics=['mse']) #train the model model.fit(X_train, y_train, batch_size=64, epochs=20, validation_data=(X_test, y_test)) #Evaluate the model score = model.evaluate(X_test, y_test, verbose=0)

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Source

Hugging Face

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