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I have followed this tutorial https://www.youtube.com/watch?v=QIUxPv5PJOY to predict the stock price of Apple one day into the future. The code is: x_train.append(train_data[i-60:i, 0]) #Will conaint 60 values (0-59) y_train.append(train_data[i, 0]) #Will contain the 61th value (60) if i <= 60: print(x_train) print(y_train) print()
Predict stock market prices using RNN model with multilayer LSTM cells + optional multi-stock embeddings.
17 Νοε 2023 · By leveraging the vast amount of historical data and identifying patterns and trends, machine learning models can offer valuable insights into future price movements. This article will provide an overview of machine learning techniques and how they can be applied to predict stock prices.
Description: Build a predictive model using machine learning algorithms to forecast future trends. This could be predicting stock prices, sales, or any other time series data. Tech Stack: Python, TensorFlow/Keras, scikit-learn, Pandas, Matplotlib.
14 Δεκ 2023 · Price forecasting uses historical data, statistical methods, and various analytical tools to estimate future prices of specific products, services, or assets. The goal is to accurately predict future prices, enabling businesses to make strategic decisions regarding production or marketing.
