Data in Machine Learning

Data is the collection of facts/observations used to train ML.
  - Numerical Data: Integer or floating value.  Ex: 14500, 6.7, 37°C
  - Categorical Data: Represents categories.   Ex: Male/Female, Yes/No
  - Ordinal Data: Ordered categories.          Ex: Poor < Average < Good < Excellent.
  - Time Series Data: Collected over time.     Ex: Stock prices per day
  - Image/Text Data: Image, PDF, Audio, Video. Ex: MNIST digit images

Tools for Machine Learning:
  Programming language     → Python
  Data Handling            → Pandas, NumPy
  Visualization            → Matplotlib, Seaborn
  Machine learning         → Scikit-learn
  Deep learning            → TensorFlow, PyTorch
  Development Environment  → Jupyter Notebook.