Machine Learning

Machine learning is a subset of AI that applies mathematics to large datasets to find trends and patterns while mapping inputs to outputs. 

Such as, given these features of a home, age, location, and the number of bedrooms as input, what will the selling price be? This means computers can produce output without being explicitly programmed by a developer or software engineer. 

Model

The mappings uncovered between the inputs and outputs are stored in a mathematical model, simply called the Model. 

Implementing Machine Learning project has two options:

1. Train a model from Scratch

2. User a pretrained Model

Pretrained Model sources:

1. ModelZoo.com

2. AWS Marketplace 

3. Hugging Face

Train a custom model (Creating model from Scratch)

1. Using Python

2. Using R

3. Using Java

To work with Phython, the environment is Jupyter Notebook

Machine Learning Framework Libraries:

1. scikit-learn 

2. TensorFlow

3. MXNet 

4. PyTorch

5. Keras