What do you like best about the product?

I use Anaconda AI Platform for a research project to manage packages with dependency conflicts. I find that conda, in particular, helps me isolate certain packages in their compatible Python versions, which makes it extremely easy and reproducible. I also appreciate using Anaconda environments on Lightning AI because the ease of use and compatibility with GPUs out of the box stand out to me. It saves me a lot of time, especially on cloud environments where I would have to recompile CPython every time I use a new VM. Switching from CPython to Anaconda was a great upgrade, and I found that setting up Anaconda AI Platform was seamless, much easier than compiling my own Python.

What do you dislike about the product?

I haven't explored it too much so I don't think I can answer that properly, but here's something that was a pain point: Wouldn't it be better if pip packages were somehow integrated into conda?

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

I use Anaconda AI Platform to manage package dependency conflicts, making package management easy and reproducible. It saves me time by avoiding manual compilation of Python versions and is seamless in setup. I appreciate the GPU compatibility and ease of use in cloud environments.

What do you like best about the product?

I really like the reliability and simplicity of Anaconda AI Platform in managing complex data science projects. The ability to create, isolate, and reproduce environments has significantly reduced bottlenecks for me. I also appreciate the curated package ecosystem and the built-in security scanning, which provide confidence when using open-source libraries. The platform's reliability ensures environments behave consistently across various phases, and its simplicity lowers the barrier for onboarding and accelerates project startups. The security feature reduces the risk associated with using open-source packages, giving visibility into known vulnerabilities and ensuring that libraries come from trusted, vetted sources. Additionally, the initial setup was really straightforward.

What do you dislike about the product?

Environment resolution and package installation can occasionally be slow, particularly for complex environments with many dependencies. Clear documentation and guided workflows for deployment integrations would help reduce start/set-up time and improve discoverability.

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

I use Anaconda AI Platform to manage data science workflows, handling environment management and dependency conflicts. It simplifies onboarding, speeds up project startups, and reduces risks with open-source packages through built-in security. Reliability and a curated package ecosystem help maintain consistent environments.

What do you like best about the product?

The platform gives us access to pre-validated and verified Python package distributions, which is crucial for building our fraud and risk models on secure and auditable dependencies.

What do you dislike about the product?

Integrating logging with external monitoring systems can occasionally demand more detailed manual configuration than I would prefer.

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

The standardization of our development environments has drastically reduced the time spent resolving dependency conflicts, allowing me to focus more hours on optimizing algorithms.

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?

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?

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 find Anaconda AI Platform incredibly impactful and accessible, making it suitable for both beginners and those seeking to further their knowledge. Its speed availability is one of the standout features, as it allows me to run scripts efficiently and tackle a variety of projects without system restrictions. The backend support is another aspect I appreciate, as it provides the necessary power and flexibility for my project needs. Additionally, the initial setup of Anaconda AI Platform was easy, which is a significant advantage, allowing me to get started quickly without encountering hurdles.

What do you dislike about the product?

I dislike the current user interface of the Anaconda AI Platform. It lacks the functionality to view code in action in real-time, a feature that is more streamlined and user-friendly in platforms like Streamlit or Replit.

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

I use Anaconda AI Platform to run scripts and learn with ease, benefiting from its speed and backend features. It allows me to tackle various projects seamlessly, without restrictions, providing an impactful and accessible platform for both beginners and advanced users.