LSTM & Mean reversion for stock price prediction.

Prerequisites

• Data: Data has to downloaded online. Due to large size of the data it has been ignored from the source control.

For the model, data can contains parameters like data, open, close, high, low, and adjusted close.

• Miniconda should be installed on your system. You can download Miniconda from the official Miniconda website.

Installation

Follow these steps to set up the project environment and install the required packages.

Step 1: Download and Install Miniconda

1. Download the Miniconda installer for your operating system from the Miniconda website.
2. Run the installer and follow the installation instructions.

Step 2: Set Up a Conda Environment

1. Open your terminal or command prompt and move to the preferred directory as your virtual environment will be set up inside your current working directory.

2. Create a new conda environment with Python 3.8 (or your preferred version) by running the following command:

   conda create --prefix ./env

3. Activate the newly created environment: bash conda activate ./env

Step 3: Install Required Packages

1. Ensure you are in the root directory of your project where the requirements.txt file is located.

2. Install the required packages using the following command:

   pip install -r requirements.txt

Step 4: Setting up Tensorflow (MacOS)

1. Install X-Code setup tools

   xcode-select --install

2. Install tensorflow and its dependencies

   conda install -c apple tensorflow-deps
   pip install tensorflow-macos
   pip install tensorflow-metal

3. Install jupyter deps and run jupyter notebook from where you can access the model

   conda install -c conda-forge -y pandas jupyter
   jupyter notebook

ToDo

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