With machine learning and AI being very popular and hyped, it's not surprising that cloud providers such as Azure, Google Cloud, and AWS offer services for doing machine learning. These services often don't require the user to delve into mathematically complex topics such as convolutional neural networks and back propagation.
Currently, I'm doing training on AWS for the Associate Developer Certification as part of company training. While the likelihood of hitting machine learning services on the exam is low, I find it to be a good idea to cover an overview in general. I won't go over every services, but hopefully you would be able to distinguish the major ones.
by Joseph Woolf
With the rise of Siri, Google Home, Alexa, and Cortana, it's obvious that there's a demand for chatbots. In the past, chatbots were more of a niche technology due to limited functionality. With recent advancements in computer technology, chatbots have now become practical for everyday use.
Most of the models in machine learning requires working with numbers. After all, much of the machine learning algorithms we've seen are derived from statistics (Linear Regression, Logistic Regression, Naive Bayes, etc.). Additionally, machines can understand and work with numbers a lot easier than us human.
However, machines just process the numbers and execute algorithms. They don't interpret the numbers returned. They don't understand the context of the data. They especially don't understand human intricacies and can easily be taken advantage by rouge players.
So then, is it actually possible for computers to understand humans? Can we ever have conversations with computers? In a sense, we already can! This is thanks to a branch of AI called Natural Language Processing.