Step 0 - Getting Started
Homebrew is a package manager for Mac OS X. Here's how to install it beforehand.
Next, let's upgrade our default installation of Python to something greater than 2.7.
Step 1 - Install Libraries
Pip
Pip is a package manager for Python.
easy_install pip
Numpy
NumPy supports scientific computing and linear algebra support.
pip install numpy
gfortran
We need gfortran to compile SciPy, but it does not come pre-installed with Xcode. Therefore, Homebrew can help us out again:
brew cask install gfortran
Scikit
Scikit-learn's purpose is to support machine learning, and therefore it's used for many of the tasks performed routinely in machine learning. A few key features are:
- It works well with the libraries stated above.
- It helps integrate the algorithms we will use for predictive models.
- It contains methods that will help us pre-process data, measure the performance of our models, and splitting data into test sets.
- Methods for creating trained models, tuning models, and identifying which features within the models are essential.
pip install scipy
Matplotlib
To install matplotlib, we need to install pkg-config
brew install pkg-config
Mat plotlib is a 2D publication library that produces high-quality graphics.
pip install matplotlib
Pandas
Pandas is a data manipulation tool that uses data frames to access and analyze information.
pip install pandas
OpenCV
Library often used for Computer Vision.
brew install opencv
Tensorflow
TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks.
pip install tensorflow
Keras
Keras is a high-level neural networks API, written in Python, and capable of running on top of TensorFlow.
pip install keras
![List of favorite AI-assisted Content Generators](/content/images/size/w800/2023/02/list-ai-content-generators.png)
![Install Octave on a Mac using Homebrew for Machine Learning Prototyping](/content/images/size/w800/2020/11/octave-machine-learning.png)
![Installing Jupyter on a Mac using Homebrew](/content/images/size/w800/2018/12/PIA21978.jpg)
Where to learn about Deep Learning
I've been stumbling upon all of these great resources so I'm deciding to make a simple list. If there's anything else I...