An overview of model explainability and interpretability fundamentals, AI applications, and biases in AI model predictions. We looked at utilizing SHAP and LIME to explain a Logistic Regression model and how to explain and interpret an ensemble model.
Learn how to make a password generator in Python with the ability to choose the length of each character type using the built-in random, string and argparse modules.
Learn how to build a simple dictionary application using Django web framework and PyDictionary library in Python.
Learn the pros and cons of Python and Javascript programming languages when it comes to web scraping.
Learn how to build a planet simulator using pygame library in Python
Learn how to build a UI-based typing speed tester in Python using the built-in Tkinter library.
Learn how to perform dimensionality reduction with feature selection such as recursively eliminating features, handling highly correlated features, and more using Scikit-learn in Python.
Learn how to replace text in Word document files (.docx) using python-docx library in Python.
Learn how to build the frontend of a CRUD application using Flask, Jinja2, Bootstrap and SQLAlchemy libraries in Python.
Learn how to make a calculator app with various features such as history and formulas using Tkinter library in Python.
Learn how to make a simple file explorer that is able to navigate through folders, create folders and files and more using Tkinter in Python.
Learn how to make a simple drawing tool with brush color and size changing feature using PyGame library in Python.
Learn how to build a simple text editor that opens and saves text files using Tkinter library in Python
Learn how to combine psutil and Scapy libraries to make a network traffic monitor per network interface and per process in Python
Learn how to make buttons in PyGame that support pressed calling (multi pressing) and one-shot pressing in Python.
Learn how you can perform K-Fold cross validation technique using the scikit-learn library in Python.