Web-based application to host a trained coastal forecast machine learning model.

Anaconda makes it easy to install TensorFlow, enabling data science, machine learning, and artificial intelligence workflows. TensorFlow with conda is supported on 64-bit Windows 7 or later, 64-bit Ubuntu Linux 14.04 or later, 64-bit CentOS Linux 6 or later, and macOS 10.10 or later.

1. Download and install Anaconda or Miniconda.
2. On Windows open the Start menu and open an Anaconda Command Prompt. On macOS or Linux open a terminal window. Use the default bash shell on macOS or Linux.
3. Choose a name for your TensorFlow environment, such as "tf".
4. To install the current release of CPU-only TensorFlow, recommended for beginners:

conda create -n tf tensorflow

conda activate tf

• Or, to install the current release of GPU TensorFlow on Linux or Windows:

conda create -n tf-gpu tensorflow-gpu

conda activate tf-gpu

• TensorFlow is now installed and ready to use.

The environment will be activated, and you should see the environment variable in place of "base", i.e.:

• (tf) C:\Users\...>

For using TensorFlow with a GPU, refer to the TensorFlow documentation on the topic, specifically the section on device placement.

Creating conda environment with YAML file:

conda env create -f environment.yml

conda activate "environment name"

Creating pure Python virtual environment with requirements.txt file (non conda environment):

pip install -r requirements.txt

(Windows): env\scripts\activate.bat

(Linux or MacOS): source env/bin/activate

For MacOSX M1, refer to this video by Jeff Heaton.

• Running run.py will activate the Flask server
• Follow the link provided by IDE, terminal/console, or copy and paste the line below into your browser.
   127.0.0.1:5000