Anaconda AI Platform Reviews & Product Details

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

1) Anaconda gives immediate access to a large, vetted collection of open source packages commonly used in data analysis, machine learning, data science and AI.

That means you don’t have to manually install, and configure everything.

2) Through its package/environment manager (Conda), Anaconda makes it easy to create isolated environments per project, control package versions, avoid dependency conflicts, and ensure reproducibility across machines.

3) Because many data-science and ML libraries come pre-packaged or easily installable, you can start coding, data-analysis, or model prototyping almost immediately without spending a lot of time on installation and setup. This is especially useful when dealing with data preprocessing, exploratory analysis, or quick experiments.

4) Ease of Use is generally strong: I find Anaconda easy to use and its interface intuitive, especially for data-science work.

5) Ease of Implementation is good: It bundles many common libraries and tools, so setup is quick and you can start working quickly (no need to install everything manually).

6) Customer Support is OK but not exceptional: Support and documentation exist; community support and docs are often used.

7) Frequency of Use is high: I use Anaconda daily for data analysis, ML, or research work especially because of convenience of environments, libraries, and notebooks.

8) Number of Features is very good: It offers a wide set of pre-installed libraries, supports multiple languages, IDEs/notebooks, environment management, covering most data-science needs.

9) Ease of Integration is solid: I see that Anaconda integrates well with data-science tools, notebooks, and other workflows, allowing smooth setup of environments and dependencies. Review collected by and hosted on G2.com.

1) Not always the most up-to-date or flexible package versions.

Because Anaconda uses curated repositories, sometimes the “latest” packages are not immediately available which might matter if you rely on the newest features or fixes.

2)Large installation size.

Anaconda tends to install a big bundle of packages by default. That consumes a lot of disk space and can lead to heavy RAM/CPU usage, sometimes noticeably slowing down even light tasks. Review collected by and hosted on G2.com.

My journey with Anaconda started in a very unusual way — through a recommendation from an Instagram influencer who promoted it as the best entry point for beginners. I was skeptical, but I decided to give it a try. What I truly love is that Anaconda bridges the gap between a complete novice and the complex world of programming. I remember my first experience: unlike other tools where I got stuck on installation errors, Anaconda worked perfectly on the first try. That feeling of immediate success was incredibly empowering. Even though my job isn't 100% coding-related, I recently received a newsletter from Anaconda that actually worked — it brought back those warm memories of my first steps. It motivated me to return to "vibecoding" using their platform because it feels safe, inclusive, and hassle-free. Review collected by and hosted on G2.com.

or a "vibecoder" or a hobbyist like me, it is hard to find real flaws. However, if I must be objective, the Anaconda Navigator can sometimes be a bit heavy and slow to launch on older machines compared to lightweight code editors. But considering it carries the entire ecosystem inside, I accept this trade-off for the convenience it provides. Review collected by and hosted on G2.com.

I love how the Anaconda AI Platform allows me to seamlessly swap between different runtimes that involve multiple packages, which would typically conflict with each other. This is incredibly valuable for my AI projects, such as when I need to work with object detection and large language model packages simultaneously. I appreciate the ability to save my project runtimes and run them on any device, which provides unparalleled flexibility and ease of access. Swapping between projects with just a single click is a feature that enhances my workflow significantly. Furthermore, I find assembling environments without running into package compatibility issues to be a significant advantage that simplifies project setup and execution. The initial setup of Anaconda AI Platform was pretty easy, which made it hassle-free to start my projects. Overall, these features collectively enhance my productivity and streamline complex AI project workflows. Review collected by and hosted on G2.com.

I sometimes find that the Navigator UI doesn't work as intended, which forces me to access features through other means. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

I appreciate the Anaconda AI Platform's easy-to-use interface, which significantly enhances my data analytics work. The integration of its AI system within Jupyter Notebooks is particularly useful and makes my tasks more efficient. Additionally, the initial setup of the Anaconda AI Platform was very easy, which made transitioning to this platform smooth and hassle-free. The overall user experience is positive enough that I would highly recommend Anaconda AI Platform to friends or colleagues, as reflected in my high recommendation score of 10. Review collected by and hosted on G2.com.

I dislike the loading time of the main page for the software application, which can be inconvenient. Review collected by and hosted on G2.com.

The Anaconda AI Platform enables AI development that is both effective and convenient. It can seamlessly integrate with machine learning frameworks that are popular with data scientists and enables streamlined setting-up and managing of complex data science projects, allowing users to focus more on developing models, rather than managing the underlying system configuration. Review collected by and hosted on G2.com.

I don't like that the Anaconda AI Platform can be overwhelming sometimes, especially to people who haven't used the software before. There is a lot of content to learn, and not everything feels very "intuitive." When working with large datasets, I find using the platform can be slower than I prefer, which can impact productivity. Review collected by and hosted on G2.com.

Anaconda AI Platform provides a complete environment for managing data science and AI workflows. Its package management and environment handling are seamless, making it easy to install, update, and manage libraries without dependency conflicts. I especially value the large ecosystem of pre-built packages, Jupyter integration, and the ability to quickly prototype, test, and deploy models. It saves a lot of setup time and improves productivity, particularly for Python-based AI development. Review collected by and hosted on G2.com.

While Anaconda is excellent, it can sometimes feel heavy—especially in terms of storage space and environment size. Package downloads can be slow, and certain updates may break compatibility with older environments. The enterprise edition could also benefit from more streamlined integration with cloud platforms and better optimization for large-scale distributed workloads. Review collected by and hosted on G2.com.

I use the Anaconda AI Platform for learning and testing purposes, and it helps me create KPI dashboards and reports. I'm really happy and grateful for how it supports me in making charts and analyzing data, especially for LinkedIn. It's very useful for creating dashboard charts and handling heavy Excel sheets without hanging, showing real-time results without needing extra software. I also appreciate that I can connect easily with most databases. The platform's easy setup, without blocking services on Windows, is a major plus. Using Anaconda is a game-changer for learning new things and exploring opportunities. It's very easy to install, and I'm happy with the platform overall. Review collected by and hosted on G2.com.

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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. Review collected by and hosted on G2.com.

It might be cool to automatically suggest the user restart the kernel when updating/replacing files related to the codebase of the current project. Review collected by and hosted on G2.com.