Anaconda Reviews

We primarily use the solution for deep learning and machine learning.

The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly. 

We extensively use TensorFlow and Pytorch as the modules. 

I have nothing to say about improvements; I love this product. It's our bread and butter and we use it every day.

We did have issues with virtual environments in the past, but that has worked itself out.

I've been using the solution for 15 years.

The solution is pretty stable. A lot of our production is on Anaconda only.

The scalability of the solution is good. We have about 100 technicians on it. At this time, we don't plan to increase usage.

We've never had to reach out to technical support.

We did not use a different solution.

The initial setup was straightforward. Deployment takes a few hours.

We handled the deployment ourselves.

We use various deployment models but mostly work with hybrid models.

We don't rely on Anaconda's deployment defense a lot. We use the solution mainly for Python distribution and deployment monitoring internals. We deploy in Docker and scale it.

It's one of the best tools available out there. If you have to get started very quickly, it's great. Almost everything is ready for you to use. I think it's a wonderful tool for developers to get started with.

I'd rate the solution nine out of ten.

The best platform for a data scientist for development purposes. It supports applications which are needed for data analytics like Jupiter and predictive analytics like R.

It creates a good environment for a data science student to teach predictive and data analytics on one platform. 

Many data science applications on one single platform. This provides a platform for learning and development in the data science domain.

• Currently, it's working perfectly on Microsoft Windows but lags in open source OS like Ubuntu, Mint.
• File uploading feature needs to be improved.

Stability is good.

Scalability is the best.

Technical support is good.

Previously, we were using RStudio, PyCharm for data science domain, but with this software, we've got a perfect platform to teach data science.

The initial setup was complex.

In-house one.

Good.

We did not evaluate other options.

Voice Configuration and Environmental Management Capabilities are the most valuable features. 

If we want to do some big applications, then we need to install a lot of packages. It also takes up a lot of space.

I have been using Anaconda for six years. 

It is a scalable solution. 

The initial setup is straightforward. The deployment took twenty to thirty minutes.

Overall, I rate the solution a nine out of ten.