# here we are going to learn about machine learning in Python
# we are going to make an AI program
# a machine learning project involves a number of steps
# These steps include:
# 1. Import the data - this often comes in the form of a csv file or text file. usually from a database
# 2. Clean the data - this involves removing duplicated data or unnecessary code. otherwise our model will learn bad patterns in the data and could preduce the wrong result
# 3. Split the data into training/testing sets - we need to make sure that our model produces the right result
# 4. Create a model - we need to select an algorithm to analize the data. there are many algoithms to choose from depending what you are working with
# 5. Train the model - we train the data to find patterns in the data we give it
# 6. Make predictions - we ask the model to make predictions on what it thinks it knows. predictions are not always accurate
# 7. Evaluate and Improve - we need to imporve the model's predictions. we do this by either selecting a different algorithm that gives more accurate results or fine-tune the parameters of our model. every algorithm has perameters that we can modify
# now we will look at the libraries and tools for our project
# there are many libraries to choose from for our algorithms including:
# Numpy - this provides a multidementional array (considered very popular in the python community)
# Pandas - this a data analysis library that uses the concept 'data frame' which is a two-dimentional data structure (similar to an excel spreadsheet. also popular)
# MatPlotLib - this is a two-dimentional plotting library used for creating graphs and plots
# Scikit-Learn - this provides all the common types of algorithms (also popular)

# machine learning in python requires working in a different programming environment. vsCode makes it hard to see the results in the terminal
# the environment we will be working with is Jupyter. this programming environment makes it easier to inspect our data
# to open Jupyter, go to a terminal and type in "jupyter notbook" or search for it on windows search bar
# when you run it a window on your browser will popup accessing a server
# you will see all your files and directories from your computer. got to desktop and 'new' on the side then click python 3 to start a new notebook
# Rename the notebook to 'HelloWorld'
# this will be the file for our machine learning project
# Proceed with the course on Jupyter