![]() ![]() Once it’s downloaded, just follow the prompts. However, the Community version should work just fine if you mostly do Python development. You can take advantage of this benefit, if you’re in a similar situation. I work for a non-profit educational institute, so I have access to the Professional version. Depending on your OS, you need to download the correct version. To install P圜harm, you can go to the P圜harm website. I’ll try my best to be concise, because it’ll be overwhelming for beginners if I pour too much information. I’ll first introduce the installation and then discuss the role of each tool. Specifically, we’ll use three tools: P圜harm, Anaconda, and JupyterLab. But probably it’s something that you can try first if you have no ideas about your configurations. Certainly, it won’t be a one-size-fits-all solution for all of you. In this article, I’d like to share the combination that I’ve found to be suitable to my needs for my data science projects. ![]() In other words, your shopping list is too long and you’re probably lost where you should get started. The problem is that there are too many choices on the market, and for learning purposes, you may have already tried different tools. After you have set up your hardware, it’s time to think about how you should pick the software that you need to start your data science projects. It’s true to data science researchers too. Don’t get me wrong - we always want to improve our productivity - with the same amount of time, we can get more work done. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |