I have published numerous articles on AI and related topics and am committed to staying up-to-date on the latest research and advancements in the field.

"Don't start with definitions and theory. Instead, start by connecting the subject with the results you want." If you've read some of my articles, you may have noticed I love theoretical AI. It has a philosophical touch to it that amazes me. I like to ponder about the future of the field and what it'll mean for us.

"Attention takes two sentences, turns them into a matrix where the words of one sentence form the columns, and the words of another sentence form the rows, and then it makes matches, identifying relevant context." Check out the graphic from the Attention is All You Need paper below. It's two sentences, in different languages (French and English), translated by a professional human translator. The attention mechanism can generate a heat map, showing what French words the model focused on to generate the translated English words in the output.

The first thing you need to know is some basic language because in AI you have to talk to computer. Therefore you need to have a knowledge of a programming language. It doesn't matter which language, you should know one language so it will be easier for you to learn another language. Click here to check top 5 languages for AI. If you know Java of course it is easier for you to learn other languages because one of the most difficult language if you know it's easy to another.

Welcome to part five of Learning AI if You Suck at Math. If you missed parts 1, 2, 3, 4, 6, and 7 be sure to check them out! Convnets are the workhorses of computer vision. At TensorFlow Summit 2017, a researcher showed how they're using a convnet to detect skin cancer as well as a dermatologist with a smart phone! So why are neural networks so powerful? So what's pattern recognition and why do we care if it's automatic? Patterns come in many forms but let's take two critical examples: In image processing pattern recognition is known as feature extraction. When you look at a photo or something in the real world you're selectively picking out the key features that allow you to make sense of it. This is something you do unconsciously. When you see the picture of my cat Dove you think "cat" or "awwwwww" but you don't really know how you do that. Your built in neural network knows this is a cat. It seems simple to you because you do it every day, but that's because the complexity is hidden away from you. Your brain is a black box. You come with no instruction manual.

If you read the first article in this series, you're already on your way to upping your math game. Maybe some of those funny little symbols are starting to make sense. Also be sure to check out parts 3, 4, 5, 6 and 7. But here's another dirty little secret nobody tells you about AI: If you're a developer or sys-admin you probably already use a lot of libraries and frameworks that you know little about. You don't have to understand the inner workings of web-scraping to use curl.

Since Klaus Schwab drew attention to the arrival of the 4th Industrial Revolution in January 2016, we are witnessing the significant impact of Artificial Intelligence and its more well known subset, often seen as its synonym of Machine Learning that led Andrew Ng to propound " AI is the new electricity". India created the IITs in the 1960s that helped some Indians to achieve places of eminence in the technical and business world of the 3rd Industrial Age. Today, India is a ' KRANTI' nation poised to play center-stage in the AI age leveraging the opportunity as a ' learning movement' amongst its masses, evidenced by the rapid adoption of the mobile phone. A group of former IIT faculty and students led by Prof. M.M. Pant have started a movement of AI awareness and lifelong learning to spread knowledge about AI as per one's need. Their Mission 2020 is to prepare not only the young but all ages for their future in the 4th Industrial Age.

Every number that goes into a tensor/container bucket is called a "scalar." A scalar is a single number. Why don't they just call it a number you ask? Maybe math peeps just like to sound cool? Scalar does sound cooler than number.

If you're like me, you're fascinated with AI. Maybe you'd love to dig deeper and get an image recognition program running in TensorFlow or Theano? Perhaps you're a kick-ass developer or systems architect and you know computers incredibly well but there's just one little problem: I share your dirty little secret and I have some books and websites that will really help you get rolling fast. Like many folks, my love of intelligent machines didn't come from calculus class. It sprang from science fiction.