Best IDE for Data Science Projects
October 07, 2021
Best IDE for Data Science Projects
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Anaconda
Anaconda is the best tool for the data scientist to [develop] the machine learning project [under] a single umbrella. It is used [throughout] the whole organization. We are using the Anaconda for Python [and] R to do the data science activities end-end process, i.e. importing the statistical/ML/Visualization libraries to train and visualize the data/reports.
- Almost all required libraries are available in it.
- Easy to create a notebook for a data science project.
- [It is] flexible to work on multiple Python environments based on your requirements.
- In [the] community, [it is] easy to find the forum [and] events.
- [The] application [takes a lot of] time to load the first time.
- Sometimes, it [stops working because it] consumes more ram.
- [I would like it to] add some ready-made use case environments.
- Supports multiple environments
- All kinds of data science libraries found easily
- Doesn't stop development [on] the ML project
- Anaconda is [a] leading platform in [the] data science industry.
- It [has] good impact [across my] organization.
- [It] provides all tools [under a] single umbrella.
In Anaconda, [it is easy] to find and install the required libraries. Here, we can work on multiple projects with different sets of the environment. [It is] easy to create the notebook for developing the ML model and deployment. Right now, it is the best data science version control tool in the IT software market.
Do you think Anaconda delivers good value for the price?
Yes
Are you happy with Anaconda's feature set?
Yes
Did Anaconda live up to sales and marketing promises?
Yes
Did implementation of Anaconda go as expected?
Yes
Would you buy Anaconda again?
Yes