The last decade, if nothing else, has been a thrilling adventure in science and technology. The first iPhone was released in 2007, and back then all of its competitors had a physical integrated keyboard. The idea of touchscreen wasn't new as Apple had similar prototypes before and IBM came up with Simon Personal Communicator in 1994. Apple's idea was to have a device full of multimedia entertainment, such as listening to music and streaming videos, while having all the useful functionalities, such as web and GPS navigation. Of course, all of this was possible with access to affordable computing power at the time that Apple released the first generation iPhone. If you really think about the struggles that these great companies have had in the last 20 years, you can see how quickly technology came to where it is today. To put things into perspective, 10 years after the release of first generation iPhones, today your iPhone, along with others, can track faces and recognize objects such as animals, vehicles, and food. It can understand natural language and converse with you.
What about 3D printers that can print organs, self-driving cars, swarms of drones that fly together in harmony, gene editing, reusable rockets, and a robot that can do a backflip? These are not stories that you read in science fiction books anymore, and it's happening as you read these lines. You could only imagine this in the past, but today, science fiction is becoming a reality. People have started talking about the threat of artificial intelligence (AI). Many leading scientists, such as Stephen Hawking, are warning officials about the possible end of humankind, which could be caused by AI-based life forms.
AI and machine learning (ML) reached their peak in the last couple of years and are totally stealing the show. The chances are pretty good that you have already heard about the success of ML algorithms and great advancements in the field over the last decade. The recent success of Google's AlphaGo showed how far this technology can go when it beat Ke Jie, the best human Go player on Earth. This wasn't the first time that ML algorithms beat humans in particular tasks such as image recognition. When it comes to fine-grained details, such as recognizing different species of animals, these algorithms have often performed better than their human competitors.
These advancements have created a huge interest in the business world. As much as it sounds like an academic field of research, these technologies have huge business implications and can directly impact your organizations financials.
Enterprises from different industries want to utilize the power of these algorithms and try to adapt to the changing technology scene. Everybody is aware that people who figure out how to integrate these technologies into their businesses will lead the space, and the rest are going to have a hard time catching up.
We will explore more of such examples in the book. In this book, we will be covering the following topics:
- Scope of machine learning
- What AutoML is
- Why use AutoML and how it helps
- When to use AutoML
- Overview of AutoML libraries