Introduction
  • What Does the Course Cover?
What is software integration?
  • Properties and Definitions: Data, Servers, Clients, Requests and Responses
  • Properties and Definitions: Data, Servers, Clients, Requests and Responses
  • Properties and Definitions: Data Connectivity, APIs, and Endpoints
  • Properties and Definitions: Data Connectivity, APIs, and Endpoints
  • Further Details on APIs
  • Further Details on APIs
  • Text Files as Means of Communication
  • Text Files as Means of Communication
  • Definitions and Applications
  • Definitions and Applications
Setting up the working environment
  • Setting Up the Environment - An Introduction (Do Not Skip, Please)!
  • Why Python and why Jupyter?
  • Why Python and why Jupyter?
  • Installing Anaconda
  • The Jupyter Dashboard - Part 1
  • The Jupyter Dashboard - Part 2
  • Jupyter Shortcuts
  • The Jupyter Dashboard
  • Installing sklearn
  • Installing Packages - Exercise
  • Installing Packages - Solution
What's next in the course?
  • Up Ahead
  • Real-Life Example: Absenteeism at Work
  • Real-Life Example: The Dataset
  • Real-Life Example: The Dataset
  • Important Notice Regarding Datasets
Preprocessing
  • What to Expect from the Next Couple of Sections
  • Data Sets in Python
  • Data at a Glance
  • A Note on Our Usage of Terms with Multiple Meanings
  • ARTICLE - A Brief Overview of Regression Analysis
  • Picking the Appropriate Approach for the Task at Hand
  • Removing Irrelevant Data
  • EXERCISE - Removing Irrelevant Data
  • SOLUTION - Removing Irrelevant Data
  • Examining the Reasons for Absence
  • Splitting a Column into Multiple Dummies
  • EXERCISE - Splitting a Column into Multiple Dummies
  • SOLUTION - Splitting a Column into Multiple Dummies
  • ARTICLE - Dummy Variables: Reasoning
  • Dummy Variables and Their Statistical Importance
  • Grouping - Transforming Dummy Variables into Categorical Variables
  • Concatenating Columns in Python
  • EXERCISE - Concatenating Columns in Python
  • SOLUTION - Concatenating Columns in Python
  • Changing Column Order in Pandas DataFrame
  • EXERCISE - Changing Column Order in Pandas DataFrame
  • SOLUTION - Changing Column Order in Pandas DataFrame
  • Implementing Checkpoints in Coding
  • EXERCISE - Implementing Checkpoints in Coding
  • SOLUTION - Implementing Checkpoint in Coding
  • Exploring the Initial "Date" Column
  • Using the "Date" Column to Extract the Appropriate Month Value
  • Introducing "Day of the Week"
  • EXERCISE - Removing Columns
  • Further Analysis of the DataFrame: Next 5 Columns
  • Further Analysis of the DaraFrame: "Education", "Children", "Pets"
  • A Final Note on Preprocessing
  • A Note on Exporting Your Data as a *.csv File
Machine Learning
  • Exploring the Problem from a Machine Learning Point of View
  • Creating the Targets for the Logistic Regression
  • Selecting the Inputs
  • A Bit of Statistical Preprocessing
  • Train-test Split of the Data
  • Training the Model and Assessing its Accuracy
  • Extracting the Intercept and Coefficients from a Logistic Regression
  • Interpreting the Logistic Regression Coefficients
  • Omitting the dummy variables from the Standardization
  • Interpreting the Important Predictors
  • Simplifying the Model (Backward Elimination)
  • Testing the Machine Learning Model
  • How to Save the Machine Learning Model and Prepare it for Future Deployment
  • ARTICLE - More about 'pickling'
  • EXERCISE - Saving the Model (and Scaler)
  • Creating a Module for Later Use of the Model
Installing MySQL and Getting Acquainted with the Interface
  • Installing MySQL
  • Installing MySQL on macOS and Unix systems
  • Setting Up a Connection
  • Introduction to the MySQL Interface
Connecting Python and SQL
  • Are you sure you're all set?
  • Implementing the 'absenteeism_module' - Part I
  • Implementing the 'absenteeism_module' - Part II
  • Creating a Database in MySQL
  • Importing and Installing 'pymysql'
  • Creating a Connection and Cursor
  • EXERCISE - Create 'df_new_obs'
  • Creating the 'predicted_outputs' table in MySQL
  • Running an SQL SELECT Statement from Python
  • Transferring Data from Jupyter to Workbench - Part I
  • Transferring Data from Jupyter to Workbench - Part II
  • Transferring Data from Jupyter to Workbench - Part III