![]() The same goes for if you wanted to share your work. If you were doing these experiments on your own and you eventually find something which works, you’ll probably want to be able to do it again. You try something and it doesn’t work, then you keep trying other things until something works or nothing works at all. Why are Anaconda, Miniconda and Conda important?Īnaconda, Miniconda and Conda help to create a shareable environment where you can conduct experiments so your colleague (or your future self) can reproduce them later.Ī lot of machine learning and data science is experimental. We’ll get into the specifics of each shortly. Luckily, this is where Anaconda, Miniconda and Conda come in.Īnaconda, Miniconda and Conda are tools which help you manage your other tools. If you’re thinking, I don’t even know where to start, don’t worry, you’re not alone. One for exploring the data, another for making a predictive model, one for making graphs to present your findings to others and one more to run experiments and put all the others together. Let’s say you wanted to work with a dataset of patient records to try and predict who had heart disease or not. However, when you want to create or write your own, such as, building a machine learning project, it’s important to set your computer up in the right way. Your computer is capable of running many different programs and applications. ![]() ![]() This article will go through what Anaconda is, what Minconda is and what Conda is, why you should know about them if you’re a data scientist or machine learning engineer and how you can use them. This big bad beast is what we’re going to cover in this article. ![]()
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