Machine Learning, Deep Learning, Cryptocurrency Investment, Algorithmic Trading, Neural Networks.
“Target” Data Created: # Check for NaN values: has_nan = df['Target'].isnull().values.any() print("NaN values present:", has_nan) # Check for infinite values: has_inf = df['Target'].isin([np.inf, -np.inf]).values.any() print("Infinite values present:", has_inf) # Count the number of NaN and