The Environmental Research DTP Artificial Intelligence Training Course

Welcome to the the Env-Res Artificial Intelligence Training Course GitHub page. You can find copies of the slides, and problem and solution notebooks for exercises here.

Requirements

This python-based course assumes that you're using the following tools:

• Anaconda
• Python 3+
• Numpy
• Pandas
• Scikit-learn
• Keras
• Tensorflow

Installations

Python 3+ and Anaconda

To install python 3+ and anaconda on a windows machine, visit https://www.anaconda.com/distribution/

You may use pip or install libraries from source but these won't be supported

For UNIX/LINUX, python is preinstalled. Check your version by running python --version You can download the appropriate anaconda distribution from the anaconda website, or wgetting their tarballs.

Numpy, Pandas, Scikit-learn

In the anaconda prompt for windows, or the UNIX/LINUX terminal, run the following commands

conda create -n machine_learning python=3.7
conda activate machine_learning
conda install numpy
conda install pandas
conda install scipy
conda install -c conda-forge scikit-learn

Keras and TensorFlow

This instruction set assumes you are not using CUDA-capable discrete GPUs. If you are, see the Keras and TensorFlow documentation for your installation directions.

In anaconda prompt or terminal, type the following

conda create -n deep_learning python=3.6
conda activate deep_learning
conda install -c anaconda keras

Directory Structure

The root directory contains a Deck folder, and the Day 1 and Day 2 folders that contain all the relevant problem and solution jupyter notebooks