Learning Artificial Intelligence

Last year, my partner and I designed Gump, a Voice-Commanded Bipedal Robot for our Engineering Graduation Project. Gump won first place in the Engineering Faculty for Best Project and is currently featured in Engineering News Magazine at Concordia.

The moment we saw our robot walk on two legs for the first time and respond to the sound of our voice was miraculous.

That moment is when we knew we wanted to work on artificial intelligence for the rest of our lives.

Learning Artificial Intelligence with code(love)

Learning Artificial Intelligence with code(love)

That moment is when we knew we wanted to work on artificial intelligence for the rest of our lives.

As technology grows, so does the information that is available to us.

We began working on artificial intelligence in the NLP (Natural Language Processing) domain, something that allowed machines to understand and process human language patterns. We worked on speech recognition and now we are doing text analysis using artificial intelligence.

We’ve learned that the possibilities of using artificial intelligence are endless. Learning artificial intelligence is crucial to understanding how the 21st century will unroll—Chris Dixon, a prominent venture capitalist, argues that the next 10,000 startup ideas are clear: take x and add artificial intelligence to it.

With artificial intelligence, you can get unlimited insights from Big Data. Imagine measuring the mood of iPhone Users on Twitter after Apple’s latest product launch, gauging the world’s opinion on a major event like Russia’s invasion of the Ukraine, or predicting a company’s performance based on previous financial data, without any need for a human to relay that information to us.

Imagine a world where machines can automatically process information, and present it to use in a relatable and relevant form. This is what artificial intelligence proposes.

Artificial intelligence can help us all be more informed in less time, allowing us to make quicker decisions by getting the insights and analytics we need from Big Data.

Learning Artificial Intelligence

Learning Artificial Intelligence

Because of all this, I’m excited about artificial intelligence. I want you to be as excited as I am, so I’ve decided to highlight some ways to get started with artificial intelligence using resources available online

1-NLTK with Python

NLTK stands for Natural Language Tool Kit, an open source library with lot’s of functions to help you use NLP and artificial intelligence. to solve a problem or work on a project. You must know Python to get started with NLTK. To begin your path, I recommend the Coursera class offered by Stanford University. You might want to brush up on your Python skills with this great book for Python and NLTK beginners and then level up and learn more about Natural Language Processing by looking at this book.

2- IBM Watson Sandbox

Watson is IBM’s artificial intelligence., famous for defeating two human contestants on Jeopardy by having only the Wikipedia database to answer questions. It is considered the gold standard for artificial intelligence nowadays. IBM released a sandbox version for using Watson’s APIs for 30 days, which allows you to hack away and create a cognitive application.

If you want to use Watson for your next big thing, you won’t be able to unless you’re a Series B Funded startup, but that will change in the future. The access IBM has given to Watson now bodes well for the future. The ecosystem is still evolving, but it is the gold standard of artificial intelligence, and IBM is working to make it more accessible.

3- Udacity Courses

Sign up for the free courses on Udacity for Introduction to Artificial Intelligence, and the three Machine Learning Courses offered there. There are tons of resources and a community there to answer all your questions. We personally believe that Machine Learning should be a mandatory course for every Software Engineer and Computer Science Major.

Check out the forums as well, they’re very insightful and they will help guide you step by step.

4- MATLAB’s Neural Network Toolbox

This one is costly, but if you can get a MATLAB license with Neural Network Toolbox license as an add on, you have a very powerful system to play with. NNT is an Artificial Neural Network that has amazing capabilities for your project like speech recognition, image recognition, and object detection. We loved playing with NNT for our robot, Gump.

With a few lines of code, you can create artificial “neurons” in your program. The neurons can be assigned to do several things. We created eight neurons with MATLAB, each one assigned to a specific voice command. After that, we trained the neurons by recording over 5,000 voice samples from every person we could find on campus. The more voice recordings each neuron had per voice command, the more it grew in knowledge. When we tested it, the response was just perfect! MATLAB is immensely powerful.

Those resources will help you get started with learning artificial intelligence.

Leave comments below if you found this helpful, or know of other resources!

This post was written by Yaz Khoury, the founder of an A.I startup called Summarit that uses artificial intelligence to summarize articles for students.

The author

Roger is an entrepreneur who has co-founded a social network entitled ThoughtBasin that looks to connect students looking to make a difference with organizations looking for difference makers. This experience has given him some setbacks, but also some priceless insights. He is deferring admission from the law school of University of Toronto to pursue his dream of creating impact through entrepreneurship, and he is constantly looking to learn and create, and to do more. He contributes to social entrepreneurship projects with his fellow Global Shapers, coordinates a volunteer tutoring site, and on his off time he unwinds by reading, writing, and dancing---sometimes, all at the same time. Follow him on Twitter at https://twitter.com/Rogerh1991.