Introduction to Artificial Intelligence
Tags: Machine Learning, Data Science, Artificial Intelligence, Computer Science, Programming

Introduction to Artificial Intelligence

Breaking down the various buzz words in the field

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Artificial Intelligence(AI) is changing our world today and has entered every domain from healthcare to engineering and telecommunications. It has completely changed the way we live. Before starting with AI it is really important to know what AI is and what are its elements. In this article, you will get to know about AI and its key elements like Machine Learning, Natural Language Processing, Computer Vision and much more.

AI is the creation of software the imitates human behaviors and capabilities

AI softwares try to mimic human behavior and can essentially perform tasks that a human being can.AI is used to power search engines, online shopping recommendations, digital assistance and much more. The possibilities that AI provides are endless from detecting tumors to developing solutions for climate change, you will find it everywhere.

Some of the key elements of AI include:

Machine Learning

Machine Learning is the foundation of AI in which you essentially teach the machine to make predictions based on your dataset. You split up your dataset into training and test sets and use the training dataset to train( or teach in simpler terms) your model to draw out conclusions with the provided data.

Let’s have a look at a really interesting real-life implementation of machine learning that you wouldn’t have thought of. Machine Learning is used by an Australian agricultural technology-based project named “The Yield” that used it to make local predictions about light, wind and rain and helps the farmers there decide the correct time for sowing, irrigation and harvesting in turn leading to better production of their crop. Never thought this could be done with AI? Now you must be curious to know how all this is done.

Let’s understand this with the help of a flower dataset.

Suppose you collect flower samples, label them and make a dataset with the name of the flower and its features like shape, size, color, etc. This is your dataset. Now you divide the dataset into 2 parts( not necessarily equal)- training and testing data. Train the model with your training data. How is this done? The data is processed using an algorithm that finds relations between the flower name and other features. This model can later be used to identify the flower name based on its features. After training the data you can test the accuracy of your model with the testing dataset and use the model for further predictions.

Computer Vision

Computer Vision, as the name suggests allows the computer to interpret the world visually using images, videos, cameras. It enables the computer to understand and perform automated tasks that a human can do. Let’s look at the capabilities of computer vision in a little detail.

Image Classification

Image classification means training a machine learning model to classify images based on their contents. A very simple example of image classification could be to classify images based on whether it is of a bird, cat or dog.

Object Detection

Training a machine learning model to classify individual objects within an image and identify their location with a bounding box like identifying the location of a bird in a picture

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Semantic Segmentation

An advanced machine learning technique in which individual pixels are classified according to the object to which they belong like overlaying or masking the images. This image shows an example of semantic segmentation in which different objects are overlayed with different colors.

Face Detection

A specialized form of object detection that locates human faces in an image. The face unlock in your smartphone is probably the best example of this. Another interesting example of face detection is its use to identify a person’s age and emotional state.

Image Analysis

Extracting information from images using and providing tags and captions based on the information is what image analysis is all about like “A dog on a beach” could be used to describe the image below using image analysis.

Photo by kilarov zaneit on Unsplash

Optical Character Recognition

It is a technique used to detect and read text in images and is widely used in reading scanned documents.

Anomaly Detection

The capability to automatically detect errors, unexpected and unusual events in the system like identifying unusual transactions for your bank account. Think of a system that can identify a possible machine failure and warn you ahead of time. Sounds great! Doesn’t it?

Natural Language Processing

Ever wondered how the voice assistant on your smartphone is able to recognize your voice and do the required job for you? Yes, Natural Language Processing or NLP is the answer! Natural language processing is the capability of our computer to identify the language(written and spoken) and accordingly respond to it. It can be used to determine the tone of a message, translate texts and much more apart from recognizing our speech and performing appropriate actions.

Conversational AI

Conversational AI is the capability of the computer to engage in a conversation with you. Chatbots are the best example of conversational AI where bots participate in a conversation with humans.