AI_Trader.py

import math
import random
import numpy as np
import pandas as pd
import tensorflow as tf
import matplotlib.pyplot as plt
import pandas_datareader as data_reader

from tqdm import tqdm_notebook, tqdm
from collections import deque

class AI_Trader():
  
  def __init__(self, state_size, action_space=3, model_name="AITrader"):
    
    self.state_size
    self.action_space = action_space
    self.memory = deque(2000)
    self.inventory = []
    self.model_name = model.name
    
    self.gammsa = 0.95
    self.epsilon = 1.0
    self.epsilon_final = 0.01
    self.epsilon_decay = 0.995


  def model_builder(self):
      
      model = tf.keras.models.Sequential()
      
      model.add(tf.layers.Dense(units=32, activation='relu', input_dim=self.state_size)
      model.add(tf.layers.Dense(units=64, activation='relu')
      model.add(tf.layers.Dense(units=128, activation='relu')
      model.add(tf.layers.Dense(units=self.action_space, activation='linear')