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.
- Download and install Anaconda or Miniconda.
- 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.
- Choose a name for your TensorFlow environment, such as "tf".
- 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