Why Python For AI Is The Best Language To Use For Machine Learning Algorithms?Posted by Tonnesen Stallings on June 16th, 2021 Python for AI, Machine Learning and robotics in conjunction make it extremely easy to develop advanced robotic systems. Python is currently the second most popular programming language for AI research and experimentation in Artificial Intelligence. But what makes Python so well suited to the task? And more importantly, which are the best books and programs that train a system to learn from its past data and how to continue doing so as the system is trained? In this article I will try to answer these questions and more, starting with a brief review of Python and then exploring the wider world of Machine Learning with Python. Python is a very high-level programming language, offering a high-level of flexibility and expressive power. It was designed originally for web programming, targeting lower level languages (such as Perl or C) using a high-level syntax that can be used for writing Python code. Today, Python can be used for all kinds of computer science research including artificial intelligence, large-scale robotics projects and manufacturing applications. Computational natural intelligence is the field of study that deals with designing and running artificially intelligent software and networks. Many people believe that the future of the human mind is in fact a network of billions of interacting programs, much like a complex network of human brains, in which each individual learns from its neighbors. One way to achieve this is to use large-scale programming languages to teach the human brain how to process information and make its own intelligent decisions. If we are to take this idea a step further, we might want to give our robots the ability to operate similar kinds of algorithms that would allow them to make educated guesses, form inferences, and decide on the best course of action in any situation. So if we are to develop artificially intelligent robotic androids, then we need to teach them not only how to perform basic human activities such as walking and thinking, but also how to think using smaller more intuitive steps and the like. Fortunately, it is surprisingly easy to take a piece of code and turn it into an autonomous agent. In fact, I believe that the first self-contained autonomous system, in which the entire artificial brain is contained in one program, is now under development. It will allow us to train an entire network of autonomous machines to work together and solve problems for us, all using only the simplest of programming languages. This is a relatively new technology, and while it has been around for quite some time, it was not until recently that we were able to completely write machine language using just a single programming language. One of the reasons we are still limited by the inability to write machine language using a single programming language is because it is a difficult language to learn. Machine learning requires a lot of supervised training and even then the results may not be consistent across machines. Another problem is that it is very difficult to program the type of tasks that most computers are capable of doing. This is why we have had to rely on higher-level languages like Python for AI research. We can say that Python for AI is the best language to use for teaching computers to understand the world. It covers all the areas where a traditional high-level programming language does not: image processing, statistical analysis, reinforcement learning and also feature extraction. The biggest advantage of Python for AI is that it allows you to code the entire system from a high-level programming code using a high-level tool, like the Sci Python Toolkit. It also allows you to easily reason about the program, giving you a clear picture of the behavior of the system at any time. Math & Statistics for AILike it? Share it! |