Machine learning has become one of the most important and impactful fields of Artificial Intelligence in the 21st century. It can be defined as 'the capability of a machine to imitate intelligent human behavior'. The development of machine learning algorithms has automated a myriad of computer science, data science, and data analytics practices. Machine learning exists in almost every technology used today; open any app on your phone or website on your computer and machine learning is being utilized to better enhance your experience.
Tech Kits
Beginner
Google's Teachable Machine
Length: 30 Minutes
Description: Machine learning is a technology that enables computers to recognize patterns and make decisions by learning from data rather than following fixed instructions. In this module, the concept is introduced through Google’s Teachable Machine, which makes the process accessible by allowing users to train models with examples such as images, sounds, or poses. This approach highlights how machine learning works, its presence in many aspects of modern technology, and provides a quick, hands-on experience by building an image prediction model in just minutes, making abstract ideas of artificial intelligence more tangible and practical.
Intermediate
Linear Regression on Google Colab
Length: 45 Minutes
Description: Linear regression is a machine learning technique that helps identify relationships between variables by fitting a straight line through data points, such as estimating how study hours influence exam scores. In this module, the focus is on implementing a linear regression problem to see how algorithms handle regression tasks, learning how to code a model, and visualizing its performance. This process demonstrates how machine learning simplifies complex data into clear mathematical models, making it possible to uncover patterns, make predictions, and refine accuracy in practical applications across fields like business, healthcare, and engineering.
Advanced
Random Forest Classification with Kaggle
Length: 60 Minutes
Description: Machine learning is a branch of artificial intelligence that enables computers to recognize patterns and make decisions from data without being explicitly programmed. Random Forest Classification uses many decision trees working together to improve accuracy and reliability. Each tree makes a prediction, and the combined results create a stronger overall outcome. In this module, the algorithm is applied to predict the survivors of the Titanic, showing how machine learning can be used in practical scenarios to analyze complex data and generate meaningful insights across fields like healthcare, finance, and marketing.
Resources
Python 3.5
Type: Programming Language
Description: Python is an interpreted high-level programming language for general-purpose programming. Version 3.5 is a part of the many new versions that continuously are being put out.
Google Colab
Type: Development Environment
Description: Google Colab is a code development environment that runs in the browser using Google Cloud and utilizes cloud computing.
Teachable Machine
Type: Application
Description: Teachable Machine is a Google application that allows user to train their computer to recognize their own images, sounds and poses.
Kaggle
Type: Development Environment
Description: Kaggle is an open-source subsidiary of Google that provides increased accessibility for datasets and code for Kaggle users and even offers its own web-based, Jupyter Notebooks environment for data scientists to work on projects directly on the Kaggle website.