As a AI developer I have used Anaconda for some of my projects and the feature I most like about it are:- 1) Good for projects with shared environment 2) Bundled important python libraries for AI development and Data science which really makes it easy to use 3)Strong open source community to clear doubts 4) Interactive platform for user support and new updates along with the forum 5) Integration with jupyter lab makes it more useful for AI developers

I find Anaconda AI Platform really helpful for machine learning and deep learning projects because it has a built-in interpreter with most useful packages like numpy, pandas, scikit-learn, PyTorch, and TensorFlow, so I don't have to manually install them. It also has all the IDEs accessible from its platform, making it easier to access, manage, and use. Installing new Python packages in the interpreter is easy through the Anaconda terminal. I like how the user interface is easy to navigate, which is very convenient for a beginner coder like me. This helps me as a beginner in the machine learning and deep learning domain to use different Python packages and access a variety of different IDEs. The initial setup was also very easy.

I use Anaconda AI Platform for a research project to manage packages with dependency conflicts. I find that conda, in particular, helps me isolate certain packages in their compatible Python versions, which makes it extremely easy and reproducible. I also appreciate using Anaconda environments on Lightning AI because the ease of use and compatibility with GPUs out of the box stand out to me. It saves me a lot of time, especially on cloud environments where I would have to recompile CPython every time I use a new VM. Switching from CPython to Anaconda was a great upgrade, and I found that setting up Anaconda AI Platform was seamless, much easier than compiling my own Python.