“Fall in love with the process and the results will follow.” - Bradley Whitford
From here on…
The last post in this blog column was an overview of why we would opt for AI over the traditional programming process. It also dropped hints on some common terms in this AI arena.
Here is an outline of what we will be covering the coming weeks.
With an AI model, a “machine acts as a blueprint of the human mind, by being able to understand, analyze, and learn from data through specially designed algorithms.” (IOTforAll)
This process can be achieved by:
Data can be structured or unstructured.
The AI software you choose can be in the form of “algorithms, libraries, or frameworks of code, or developer kits libraries” (G2). As per SoftwareTestingHelp, this broadly falls under 4 types of AI software:
In the table below, you will find some options for getting started to build an AI model as far as AI platforms and ML software options go. This has been further classified into pre- built models and customizable models. You could acquire a basic framework from various open sources and tweak the model as per your needs or start fresh all by yourself. It also lists the types of data (i.e. text, video/ image or audio) these options can analyze.
In the coming weeks, we will be building models for autocorrect/ spellcheck function, detecting an object/ person in an image and detecting sound in an audio clip.
Which options would you choose?
“Machine learning is the art of study of algorithms that learn from examples and experiences.” (Guru99)
Every time I read this definition, I feel fascinated observing my newborn. This is real-world training of her brain. I call out the names, or colours or action words associated with the objects she picks up. For example, I say, “This is a blue cup. We turn the lid of the blue cup to open. There is water inside the blue cup. Put your lips on here and slurp from the blue cup.” Her data set includes my dialogue and the image of a blue cup - a combination of image and sound training.
For further reading:
Aruna is A.I. For Anyone’s Mind Games column writer and is an AI enthusiast. This column covers topics on how to create basic AI models, using the available software and gain insights into common AI terms. She currently studies Computer Science at Northeastern University – Seattle. Her areas of interest in CS include AI, Data Science and Robotics.