Must Have for ML/DL, Data Analytics, Software Development and Deployment.
December 18, 2024

Must Have for ML/DL, Data Analytics, Software Development and Deployment.

Ranu Singh | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User

Overall Satisfaction with Anaconda

We're using Anaconda for software further software for our clients. Earlier, I used both R and Python, but now I am mainly using it for Python. As we have multiple applications running on multiple Python versions ranging from Python 2.x to 3.x. and with Anaconda, this becomes relatively easy with its environments. I am actively using Spyder, PyCharm, and Jupyter Notebook. Apart from this, we are actively using Anaconda on our servers to deploy any machine learning applications.

Pros

  • Data Analysis.
  • Software Development in Python.
  • Machine Learning/Deep Learning model training and testing.
  • Code Deployments.

Cons

  • Sometimes, I have reached a situation where I am unable to download dependency using pip or conda, and I have to create whole new environments.
  • Once, I faced a very weird issue where I was unable to update or Launch Spyder and tried everything, and it didn't work.
  • We're using Anaconda as open source, so it has only given us returns/profits, so there is no negative here.
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.
  • Docker
I am using both; when it comes to application deployment on the server, I use Docker, and sometimes, I use Docker with conda image for deployment when it comes to ML/DL apps.

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

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.

Anaconda Feature Ratings

8.0
Extend Existing Data Sources
8
8.5
Visualization
9
Interactive Data Analysis
8
8.0
Data Transformations
8
Data Encryption
Not Rated
9.3
Multiple Model Development Languages and Tools
9
Automated Machine Learning
Not Rated
Single platform for multiple model development
10
Self-Service Model Delivery
9
9.5
Flexible Model Publishing Options
10
Security, Governance, and Cost Controls
9

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