Stephen is a Content Developer at Udacity and has built the C++ and Self-Driving Car Engineer Nanodegree programs. He started teaching and coding while completing a Ph.D. in mathematics, and has been passionate about engineering education ever since.
Relevant are algorithms sorting how? In a sentence, word order is essential to convey the intended message. The same applies to programming: Having sorted datasets makes it possible to organize massive amounts of data while making it quickly searchable.
That’s why you often find sorting algorithms in the first pages of programming textbooks. In this article, we describe sorting algorithms, explain how they work, and illustrate how to choose the right sorting algorithm for your program.
Each year, AI practitioners compete for the Loebner prize. This is an implementation of the Turing test where a computer‘s “humanness” is assessed by a panel of judges. The machine passes the test if it manages to convince the judges that it – and not its human competitor – is a real person. How does it do this? Simply by using language. Human-like conversation is but one of the many applications of Natural Language Processing, NLP for short.
As a programmer, you’ve probably encountered some kind of an integrated development environment (IDE). Many IDEs work with multiple programming languages, while some are built for just one language, like C++.
In this article, we’ll look at the top IDEs for C++. But before we get started, let’s talk about what an IDE is in the first place.
Python AI libraries have one job: To provide the benefits of AI algorithms and tooling without any of the complexities of their implementation. No developer wants to reinvent the wheel or delve into an array of statistics and data science books every time they want to build a chatbot or classify some data. This is where the copious number of AI libraries, written for Python, can make projects faster to build, more readable and more effective at achieving their goals using AI. Read on to find out more.
Are you looking for examples of using Python for data analysis? This article is for you. We will show you how to accomplish the most common data analysis tasks with Python, from the features of Python itself to using modules like Pandas to a simple machine learning example with TensorFlow. Let’s dive in.