I use the tool for Jupyter Notebook.
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A cloud-based solution that can be accessed from anywhere
What is our primary use case?
What is most valuable?
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
What needs improvement?
Anaconda could benefit from improvement in its user interface to make it more attractive and user-friendly. Currently, it's boring.
For how long have I used the solution?
I have been using the product for five years.
What do I think about the scalability of the solution?
Four to five developers use the product.
How are customer service and support?
I haven't contacted the tool's support team for any help or questions. I primarily use it for one of its services, and I write my own code within that service, so I haven't felt the need to contact support.
How was the initial setup?
The product is straightforward and self-explanatory. Users can easily follow the next steps provided and install it without much difficulty.
What's my experience with pricing, setup cost, and licensing?
The tool is open-source.
What other advice do I have?
Some basic tutorials can be found on YouTube, which can help you understand how Anaconda services work. Watching these tutorials can make it easier for someone to use the product. Using it for the first time can be considered at a medium difficulty level, neither too easy nor too difficult. The package management system has greatly improved my development process. I can easily install and incorporate any package I need into my work. I rate the overall product an eight out of ten.
Simplifies package and environment management across operating systems
What is our primary use case?
What is most valuable?
Voice Configuration and Environmental Management Capabilities are the most valuable features.
What needs improvement?
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.
For how long have I used the solution?
I have been using Anaconda for six years.
What do I think about the scalability of the solution?
It is a scalable solution.
How was the initial setup?
The initial setup is straightforward. The deployment took twenty to thirty minutes.
What other advice do I have?
Overall, I rate the solution a nine out of ten.
Offers free version and is helpful to handle small-scale workloads
What needs improvement?
Anaconda can't handle heavy workloads. From an improvement perspective, I want Anaconda to be able to handle heavy workloads.
For some enterprise versions or wherever there is a need for cloud-based tools to deal with large amounts of data, I feel that it would be good if Anaconda has a partnership or is able to integrate with Databricks.
For how long have I used the solution?
I have experience with Anaconda for years.
What do I think about the scalability of the solution?
In my company, around 10 to 30 people were using the product.
Which solution did I use previously and why did I switch?
In my company, I use Databricks 90 percent of the time.
How was the initial setup?
I have not encountered any challenges during the deployment process of Anaconda, especially considering that I haven't worked on heavy data.
What's my experience with pricing, setup cost, and licensing?
My company uses the free version of the tool. There is also a paid version of the tool available.
Which other solutions did I evaluate?
In terms of development, Anaconda is better than Databricks because computing costs are involved while using the latter tool. If the data is not too large and if a company can work on sample scripts while ensuring that within the organization, everything gets standardized, development can be done on Anaconda, and then users can run production scripts on Databricks because it is popularly used considering the heavy data it can manage.
What other advice do I have?
I have used the product for data engineering and for ML models.
Anaconda's ability to streamline our company's workflow in data analysis has pros and cons attached to it. In terms of pros, Anaconda's advantage over Databricks revolves around the use of system resources. Everything in Databricks is on an online computing basis, where our company uses the product's resources, but our own resources aren't utilized. In our company, we have heavy machines with us, but they aren't used when we use Databricks. I think some small-scale workloads can be handled in Anaconda. In terms of the entire lifecycle, I think Databricks has a lot of advantages over Anaconda. You have features that help you revive old models or deploy your models within the same Databricks. Databricks offers an end-to-end lifecycle over Anaconda.
Working with the integrations of various libraries and tools within Anaconda, I have not faced any issues. Anaconda offers advantages to its users when the workload or data is not much. I am not sure if the paid version of the product is on a computing basis, but if it is, then there is not much of a difference between Anaconda and the other products in the market. As per my understanding, even the enterprise version can be hosted on the company servers, so there are not many costs involved.
I recommend the product to those who plan to use it. The product can be useful in multiple sectors other than the financial sector. In the financial sector, Anaconda can be useful if the workloads are very low, there are many non-priority tasks, and the data is not much used. Issues occur when teams working in collaboration want to use Anaconda and Databricks together. I can use Anaconda for non-heavy tasks. I can go with Databricks for heavy tasks. It would be good if Anaconda and Databricks could have integration capabilities. For computing, you can use Anaconda and the resources from Databricks.
I rate the tool an eight out of ten.
Complete software for data science development
What do you like best about the product?
It has a large set of apps for data science development, like Jupyter lab and Jupyter notebooks
What do you dislike about the product?
It takes a lot of time to start, and consumes high amount of CPU
What problems is the product solving and how is that benefiting you?
I use Jupyter notebook for my daily experimentations in data science work
Best software for Python and R programming.
What do you like best about the product?
Anaconda's platform is very easy to use. It can be understood pretty well by beginners which makes it beginner friendly and user friendly. Personally, I use Anaconda because it does the job even after being open source. It's package management ability is the best. One cam find every package in Anaconda environment. It's also good for using virtual environments.
What do you dislike about the product?
Although, one cannot find any disadvantages in Anaconda, there may be some problems if someone has a smaller machine. As Anacnda comes with a lot of packages, it uses a lot of space and memory.
What problems is the product solving and how is that benefiting you?
I use Anaconda for all my coding stuff. I as a AI/ML engineer, make use of Jupyter labs and notebooks inside Anaconda for building and training models.I also use VS Code, Pycharm and spyder inside Anaconda as different virtual machines for working on different data science and machine learning taska.
Coding Made Easy: Anaconda's Magic Touch for Smooth Programming!
What do you like best about the product?
I really like how Anaconda makes coding feel like a breeze. The best part is the simplicity - installing and managing all the tools I need is super easy. It's like a magic box that brings everything together for smooth coding adventures. The variety of packages and the way it handles data science tasks? Just awesome! Anaconda truly takes the hassle out of setting up, so I can focus more on my code and less on technical headaches. Thumbs up for making my coding journey so much smoother!
What do you dislike about the product?
While Anaconda is great, I've found a couple of hiccups. Sometimes, it feels a bit heavy on my computer, making things a tad slow. Also, updates can be a bit tricky - I wish it were smoother. But hey, despite these small bumps, Anaconda still rocks for coding ease!
What problems is the product solving and how is that benefiting you?
Anaconda is my coding superhero, tackling the big task of setting up and managing tools effortlessly. It saves me from the headache of installing everything separately, making coding a breeze. With Anaconda, I can easily dive into data science tasks, thanks to its cool packages. It's like having a helpful friend that takes care of all the technical stuff, so I can focus on coding fun and not worry about the nitty-gritty details. Anaconda truly makes my coding journey smoother and more enjoyable!
The best Graphical user interface to manage all my development tools and python packages.
What do you like best about the product?
Anaconda has a really usefule and good user interface which helps in knowing what tools have been installed and what pakages have been installed on a certion development environment.
What do you dislike about the product?
the user interface can have much more featuers and that can be worke on there is a lot of scope for growth.
What problems is the product solving and how is that benefiting you?
Anacomda mainly helps me in managing my dependencies versions in my code by helping me creating managable python environments.
Python ( use for programming or analysing )
What do you like best about the product?
its easy coding . Its environment which is free to access.
What do you dislike about the product?
Nothing here to disliken in anaconda . Its jupyter notebook is preety much good.
What problems is the product solving and how is that benefiting you?
I am using in data analysis
Anaconda Open Source Cloud Operating System
What do you like best about the product?
Anaconda is home to several open source platforms; orange, tableau,IBM watson Studio, etc. Here you can test and validate AI/ML algorithms and analytical models for deployment on cloud. These analytical models are integratable or transferable to large platforms like, AWS, IBM or Microsoft Azure, etc.
What do you dislike about the product?
There isn't much to dislike about it as it's continually being updated and can configure several AI libraries to work with.
There're several versions of it and yes shifting from one version to other may let you loose some features of your model that was run on an older version before but it lets you rebuild it.
There're several versions of it and yes shifting from one version to other may let you loose some features of your model that was run on an older version before but it lets you rebuild it.
What problems is the product solving and how is that benefiting you?
It is good at developing, testing and validating AI/ML models. I use it for research purposes.
Anaconda my ML DL starter
What do you like best about the product?
During my final year project "Identifying and marking player during live matches" I used most of the features like Spider, Notebook, Jupiter Notebook.
It's easy to implement solutions in anaconda. The latest feature that I checked recently is Anaconda is now available over clouds. Anaconda comes with CONDA which is very helpful to manage multiple environment.
It's easy to implement solutions in anaconda. The latest feature that I checked recently is Anaconda is now available over clouds. Anaconda comes with CONDA which is very helpful to manage multiple environment.
What do you dislike about the product?
Can't think of more, but screen has very less themes. Another is loading time of navigator, It took a lot.
What problems is the product solving and how is that benefiting you?
During college projects I used and Implemented " Human Identification and marking" . First I try to write codes in different IDE and text editors but professor suggest to move to notebook, spider, then anaconda solved most of my problems
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