Machine learning, a subgroup of artificial intelligence, is a growing field. There are many ways to begin learning machine learning, but to do so you must choose the right IDE for you. An IDE is an integrated development environment, or in other words, a software that allows you to code on a PC. Without further ado, here are the top five IDEs for machine learning.
5. VS Code
VS Code is a great IDE to use with machine learning especially because of its compatibility with Git. VS Code is already a popular IDE that many people know how to navigate, making it even more beneficial for machine learning. Unfortunately, the requirement to download various libraries and packages each time you want to start a machine learning project can be tedious. Regardless of this, VS Code is still great for machine learning.
4. R Studio
R Studio is an IDE that is great for coding in R. R is not as popular of a language for machine learning as Python. With this being said, if you aren’t comfortable coding in R, R Studio IDE isn’t the right fit for you. Nonetheless, R Studio has capabilities of high-performance computing and allows the user to work with a variety of file types.
3. PyCharm
PyCharm is known for its use in data science projects and its ability to work with large datasets. PyCharm allows the user to use an existing Python environment or create a new one. It is overall really easy to use and has many nice features. One of these features is its ability to disable unneeded tools. This can help remove some of the overwhelming amount of clutter that may appear on your screen.
2. Jupyter Notebook
Jupyter Notebook is known for its ability to utilize over 100 different programming languages and its speedy code output. Additionally, Jupyter Notebook is good with complex math involving complexities like matrices. Jupyter Notebook also splits up its code in a step-by-step basis making it easier to code.
1. Spyder
Spyder is a great IDE for machine learning because of its easy to use layout and its constant updates. Spyder also has a multi-language editor. It has the libraries for machine learning built in, so there is no need to install them. This saves a lot of time and effort. Spyder also has clear debugging communication and code analysis making it easier to code.
