What do you like best about the product?

I like the Anaconda AI Platform for its excellent support and the ability to connect to Anaconda Cloud from any device. I also appreciate the ability to easily transfer files to and from the cloud from any device. The paid version of Anaconda AI allows me to work with data sources on the internet without restrictions, which is extremely important to me. I also find that Anaconda's cloud solution is much more convenient than using a local Python development environment. The initial setup was straightforward, and I handled it easily. Moreover, I am so satisfied with the user experience that I rated the likelihood of recommending the Anaconda AI Platform to a friend or colleague as 10 out of 10.

What do you dislike about the product?

It might be cool to automatically suggest the user restart the kernel when updating/replacing files related to the codebase of the current project.

What problems is the product solving and how is that benefiting you?

I use the Anaconda AI Platform for developing analytical applications in Python and debugging them, solving the problem of code deployment and working with internet sources without restrictions. The platform offers good support and the ability to work with Anaconda Cloud from any device.

What do you like best about the product?

The batteries included approach is the biggest advantage. I find it very hepful that it pre-installs the most critical data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib) without needing to fight with dependency conflicts manually. The Anaconda Navigator is great for managing separate environment, Eg- I can keep my deep learning environment separate from my standard stock analysis environment.

What do you dislike about the product?

It can be quite heavy on system resources. The base installation consumes a significant amount of disk space. Also the Navigator GUI can sometimes feel sluggish to load on older hardware. The 'Solver' (used for resolving package dependencies) can occasionally be slow when installing new packages.

What problems is the product solving and how is that benefiting you?

I use it primarily for financial data analysis and predictive modeling for the stock market. It solves the problem of 'Environment Hell' by allowing me to quickly spin up isolated Python environments for different projects (e.g., one for Kaggle competitions, one for analyzing NSE stock data). It simplifies the workflow so I can focus on the algorithms rather than the setup.

What do you like best about the product?

I love this platform for its powerful and robust tools to synthesize data to a more reasonable output that supports active decision making. Its interface allows co-ordination and co-operation of teams to efficiently collaborate on projects. Though there are lots to say about this platform, I feel that it is worth mentioning about the Anaconda AI Assistant that allows us to create a basic template from where we can customize further to make a complete program is really commendable. I really love its capability to export and run the chat in notebooks.

What do you dislike about the product?

I love most part of this platform but the price of purchasing separate packages can be high. I also would say that lots of earing is really necessary to fully explore its capacity.

What problems is the product solving and how is that benefiting you?

This platform greatly assist in improving efficiency of projects. Its ability to solve critical issues in testing phase is really outstanding.

What do you like best about the product?

I really appreciate the Anaconda Navigator interface. It makes it extremely easy to launch applications like Jupyter Notebook and VS Code without using the command line. As a student it is perfect for managing libraries and environments visually. I have used it for all my engineering studies.

What do you dislike about the product?

Sometimes the software can be a bit heavy and slow to start up.

What problems is the product solving and how is that benefiting you?

It simplifies the management of Python packages and dependencies. It allows me to create isolated environments for different projects, avoiding conflicts between different versions of libraries.

What do you like best about the product?

It provides smooth, secure, and reliable environment and package management, making it easy to maintain consistent setups across all my projects.

What do you dislike about the product?

Some features feel slightly complex during initial setup, and certain workflows could be more streamlined for new users.

What problems is the product solving and how is that benefiting you?

It eliminates the common issues around package compatibility, version conflicts, and environment reproducibility. With centralized management and secure package repositories, it helps maintain a clean, controlled development environment, which leads to fewer deployment failures and smoother end-to-end workflows.

What do you like best about the product?

Honestly, what I find most brilliant about the Anaconda AI Platform is that it just eliminates the "dependency hell" that usually plagues Python development.

If you’ve ever tried to manually install a dozen machine learning libraries only to have them all break because one version of NumPy didn’t agree with another, you’ll know exactly why Anaconda is such a relief. It handles all that messy wiring for you.

Here is a breakdown of what makes it stand out, from a "day-to-day use" (I use at work every week) perspective:

1. The "Batteries Included" Philosophy
The best bit is definitely the convenience of implementation. You download one installer, and suddenly you have everything you need: Python, Jupyter Notebooks, pandas, scikit-learn and hundreds of other data science packages. You don't have to spend your first afternoon hunting down libraries; you can just open a notebook and start coding immediately. It feels like moving into a furnished flat rather than an empty house.

2. Lifesaver
While pip is great, the conda package manager is the real hero here.

Safe Experimentation: It lets you create isolated "environments" for every project. You can have one environment with an old version of TensorFlow for a legacy project and another with the cutting-edge PyTorch version for something new, and they won't interfere with each other.

Non-Python Libraries: Unlike standard Python tools, Conda can install non-Python dependencies (like C libraries) that data science packages often rely on. It saves you from having to compile things from source, which can be a nightmare on Windows.

3. Running AI Locally (Cool Stuff)
Recently, they’ve added features like the AI Navigator, which allows you to download and run Large Language Models (LLMs) directly on your own laptop. This is massive for privacy. You can experiment with AI assistants without sending your data to the cloud. It turns your local machine into a private AI lab, which is incredibly empowering.

4. Agnostic and Stable
It works almost exactly the same whether you are on Windows, macOS, or Linux. This consistency is underrated but vital if you are working in a team where everyone uses different operating systems. You know that if it runs in your Anaconda environment, it’s likely to run in theirs too.

In short, I like it because it lets you focus on the maths and the code rather than the configuration. It removes the friction between having an idea and testing it out.

Note: For customer support, I have yet to experience any of it, thus I cannot comment much about it.

What do you dislike about the product?

Disclaimer: This is not anything about "dislike". It's just an experience/observation over the years. Hope it helps.

The full Anaconda installer is huge (gigabytes). It installs hundreds of packages you will likely never use. It feels a bit like buying a whole supermarket just because you wanted a pint of milk.

Perhaps this is why many of us switch to Miniconda (the stripped-down version) eventually.

What problems is the product solving and how is that benefiting you?

It solves the configuration headache. Instead of spending three days figuring out why your C++ compilers aren't talking to your Python installation, Anaconda gives you a pre-built binary that just works. It lowers the barrier to entry for maths and science enormously.

What do you like best about the product?

I like using the Anaconda AI Platform to easily open VSCode and Spyder applications, which enhances my development workflow significantly. The seamless integration of these IDEs through Anaconda makes it incredibly convenient. I find the platform's ease of use particularly valuable; it simplifies my tasks and allows me to focus more on the actual work rather than technical hurdles. The graphical features provided by Anaconda AI Platform are impressive, making data visualization and manipulation tasks straightforward and aesthetically pleasing. Additionally, I appreciate how smooth the terminal output appears when using Anaconda, which suggests a well-designed interface and efficient performance. Overall, I have no complaints about Anaconda AI Platform and find every aspect of it to be satisfactory.

What do you dislike about the product?

Nothing really

What problems is the product solving and how is that benefiting you?

I find Anaconda AI Platform convenient for launching VSCode and Spyder with ease of use and effective graphics, simplifying my environment setup and workflow.

What do you like best about the product?

As someone who works daily with data science and ML workflows, what I appreciate most about the Anaconda AI Platform is the way it brings together reliability, security, and ease of use in a single environment. The curated package ecosystem removes the constant dependency conflicts I used to deal with when managing environments manually. Having stable, pre-tested builds of key libraries (NumPy, pandas, TensorFlow, PyTorch, etc.) saves me hours of troubleshooting every month.

I also value the focus on model safety and governance, which has become increasingly important in enterprise settings. Anaconda’s approach to managing packages and controlling access to AI models gives me confidence that what I’m deploying is safe, compliant, and reproducible.

The integration between environments, notebooks, and deployment pipelines feels seamless, and the platform makes collaboration across teams much easier. For me, Anaconda is the “no-surprises” foundation for any serious data or AI project.

What do you dislike about the product?

My only complaints are that the platform can feel a bit heavy during initial setup, and package installs are sometimes slower than pip. The environment management UI could also be a bit more streamlined. Nothing major, but there’s room for small usability improvements.

What problems is the product solving and how is that benefiting you?

Anaconda AI Platform solves the biggest headaches in data science—environment conflicts, dependency issues, and concerns around model/package security. It gives me a stable, controlled workspace where everything just works. This has significantly reduced setup time, improved reproducibility across projects, and made it easier to collaborate with my team without worrying about version mismatches or unsafe packages.

What do you like best about the product?

It has multiple integrated features (PythonAnywhere for hosting, JupyterNotebook and JupyterLab, and the local distribution) that make it a great hub for Python work.

What do you dislike about the product?

Not all of its features are well described or explained to me, so I do not find myself using them too much (Ex. EduBlocks)

What problems is the product solving and how is that benefiting you?

It is helping me solve the issue with using too much different tools and softwares to achieve similar goals. By using the unified Anaconda platform, I can grow skilled and familiar with one tool that fits multiple use cases.

What do you like best about the product?

I appreciate the Anaconda AI Platform for its ability to edit query code, which significantly enhances my workflow when working within Jupyter Notebook. This feature is particularly useful because it helps me address and resolve errors instantaneously, allowing me to ask for solutions directly from the platform and receive immediate guidance on how to correct issues. This capability greatly streamlines my data analysis tasks using Pandas and makes my coding process smoother and more efficient. I also find the smooth nature of the platform contributes positively to my overall productivity.

What do you dislike about the product?

Most AI solutions have a problem that when I sit down to write code, they write it, but they do not perform ejection.

What problems is the product solving and how is that benefiting you?

I use Anaconda AI Platform for data analysis and it helps streamline processes using Jupyter Notebook and Pandas, enhancing productivity with its error-solving feature providing instant solutions.