Anaconda provides access to the foundational open-source Python and R packages used in modern AI, data science, and machine learning. These enterprise-grade solutions enable corporate, research, and academic institutions around the world to harness open-source for competitive advantage and research. Anaconda also provides enterprise-grade security to open-source software through the Premium Repository.
$0
per month
Sublime Text
Score 9.2 out of 10
N/A
Sublime Text is a highly customizable text editing solution featuring advanced API, Goto functions, and other features, from Sublime HQ in Sydney.
I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.
My CMS has a small window in which I can edit custom HTML/CSS. It can be expanded some, but not as much as I would like. It also displays all code as dark text on a white background. On a page where I am doing extensive custom coding, it is helpful to see it in a larger window and in a color-coded display so that I don't have to strain my eyes as hard. Especially when I'm trying to scan for specific elements and target issues and so that I don't have to scroll endlessly in a tiny window.
Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.
I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.
It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.
This is a programmers tool. As such a lot of the features and benefits are lost on a non-technical user. To get the most out of the tool you need to have a basic crash course in how it works and what it can do. The documentation and community are good, but it takes a bit of time to get up to speed.
Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
Never had to use their customer support before. There is ample documentation online so it's straightforward to find a solution to any problem you might encounter. For example, I needed to convert a string of HTML code to a properly formatted HTML file to "modify." Easy to do when there are so many users of the product who have needed to do that same thing before.
I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!
We've used both Notepad++ and Atom; both are great but nothing really beats the Sublime Text UI; super intuitive and friendly and does everything you need without overwhelming you with stuff you don't. Other options are free, but for our organization, it was well worth the small license cost for the persistent use of a great product.
It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.
Sublime Text has helped me to focus on specific tasks, cutting out the clutter that many other IDEs have. As such, it has helped me be a more productive employee because I don't get dazed by hundreds of buttons. I can focus on just the code.
Sublime Text is so affordable that it's a no-brainer to have an extra tool in your toolset.
The Search features of Sublime Text are so useful that it has saved me a great amount of time compared to using Find & Replace menus in Xcode, Android Studio, or Eclipse.