| Author: | Francesco Lelli |
| Learning Line: | Perceptron and Applications of machine learning. |
| Course: | AI1: Introduction to Neural Networks |
| Week: | 1 |
| Competencies: | - Understand various application of Artificial Intelligence – Understand and implement a Perceptron |
| BoKS: | 3aK1 The student understands a supervised learning process and its components. She knows how to apply such a strategy in a specific (business) context. |
| Learning Goals: | Understand what you can (and can not) do with machine learning |
Welcome to introduction to Artificial Intelligence.
We define Artificial Intelligence (in short AI) as the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
In other words, AI makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing (covered in AI2) . Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.
There is no preparation for this week. However you may want to get familiar with what is possible and what is not possible to do with AI. Please have a look at the following video:
We will start the first lecture discussing these cases as well as provide you more technical details of how certain application works.
This video is a a 8 part documentary series hosted by Robert Downey Jr. covering the ways Artificial Intelligence, Machine Learning and Neural Networks will change the world.
I hope that it will serve you as inspiration for the journey ahead.
Would you like to do something more? The full list of episodes is available here:
Looking forward to seeing you in the classes!
This is week 1 of AI1: Introduction to Neural Networks, link to the all material of the course: