I have used anaconda throughout my degree and I still use it in my work today. It has been a pleasant experience I was able to hit the ground running relatively quickly and use it for my professional needs.

As a Machine learning engineer I use all the time in my work for performing various tasks. I love the fact that I get to use all software in a single centralized unit. In it I can find my all the different IDEs and tools such as Spyder, Jupyter Notebook, Jupyter lab, R Studio.....etc. I find this extremely convenient. Aside from that it allows me to create multiple virtual environments with very minimal effort through its fantastic UI (user interface) which keeps the whole process relatively simple. I would absolutely recommend this product to any Machine learning engineer or Data scientist.

I dislike the idea that it has slow start-up time. It is noteworthy to say that it is not a major issue but never the less. It is slow to start-up. Other than that there is no major issue.

Anaconda Enterprise is a virtual environment manager which is one of the most widely used tool in the world today for data science. Many of its competitors have either lacked the variability and customer support (example R) or are still in its initial stage of capturing the worldwide market (example Dataiku - potential competitor). Anaconda supports python programming language but also integrates RStudio seamlessly. It also integrates MS SQL Server and Oracle databases, thus making it easier to execute SQL queries. Anaconda supports multiple data science/machine learning libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, etc. to perform various tasks such as statistical analysis, data mining, data exploration, feature engineering, and modelling.

Anaconda is a free and open source software which is extremely easy to install and carry out developer and analytics tasks. The Anaconda GUI is very user-friendly, whether it is the Spyder IDE, RStudio or the Jupyter Notebooks. Also, Anaconda integrates easily with other tools such as RStudio, Blue Prism RPA tool, etc. It has a vast network of supporting websites such as geeksforgeeks.com and stackoverflow.com that provides solutions to various complex issues in python/data science.

The major concern related to Anaconda is that it cannot handle large volumes of data. It takes a long time to upload large-sized datasets and computations consume too much RAM. Also, Anaconda does not provide the option to modify the processing speeds i.e. choosing GPU/TPU based on the runtime required for processing.

One of the main problem we were facing Early is that, we need downloaded and install many tools separately, that may consume much memory space. But now all the things are available in a single platform. Now things are much easy to work with. Anaconda provides all the basic features that are necessary for developers.

Anaconda provides a complete package for scripting, The main and important thing is that Everything for developing projects are available at a single place. Jupiter notebook, spider, etc. are some helpful and useful tools available in Anaconda. The tool itself is faster and more efficient than others.

I didn't find anything to dislike, But sometimes the tool crashes in between working and reloading takes much time. Anyway, the customer support is good that they reply to our queries faster without any delay.

When l first started learning python l didn't know what l would like to learn either basic python, data science, machine learning hence all l needed was a software which can cater for any needs since l have limited internet access to download and this software seemed to be all l needed

It has all ide for learning and programming with python hence a single download will cover all your python needs. It has both free and paid versions to cater for both enterprises and students who are interested in using python. Small file size Can run on low end systems without hindering quality

There is nothing that l least like about this software

if you are Beginner and Experience, To begin with, it is extremely simple to set up and use. You can start coding immediately after downloading Anaconda from the official website I usually code using Jupiter Notebook  Anaconda is less difficult to use than PyCharm. If I have small ventures, it is the best place for me. In comparison to PyCharm and other IDEs, Jupiter Notebook runs tasks much faster. Supported multiple Machine Learning libraries and Very easy to use. The best Thing About anaconda is it is free to use.

Whenever I Working with a huge amount of data it takes a bit more time to load and display the data. At first, it's a little sluggish. It would greatly improve the experience if it were a little quicker. Otherwise, I love using Anaconda.

Industry which recruits new comers more or starting new branch in data science especially, this tool can be boon to them. Very easy for beginners to get along and all-in-one package which is also compact in size.

Most of the tools like PyCharm or Eclipse etc. requires to download packages when you need during development like numpy, panda more if you need, and many new trainees face problem while setting up the dependencies. Anaconda isnsaviour for them. With already loaded packages that are frequently used and it also helps to set up dependencies in future. Setting up Anaconda and its components like Jupiter Notebook are quite easy with many tutorials available online, but even without that installation is easy. Along with Python, it supports many other popular language like R. Community support is great.

Heavy load on memory and cpu on start up. Hence, specifications need to be above average if you are using for personal use. Many functionalities are provided for free but other complex functionalities specially in the field of data science and analyticsy, it require to purchase premium services. If your code get about few hundreds of lines, it might be difficult to navigate to specific module. Need some changes like Sublime to see the text zoomed out so it would be easy to find the part in a code.

Anaconda gives me so much flexibility and I don't know what I would do without it. It is my preferred software when it comes to programming Softwares. I have used it for a while now and I am very much pleased with its functionality. The fact that is is actively supported and updated is another plus for me.

I have used Anaconda base application for all my Python programming as it offers me all the plugins that I need for coding. It gives an interface to install all the plugins in a user-friendly way. The ability to use anaconda with many other IDE is another thing that has drawn me to Anaconda. I could use it with PyCharm or Spyder.

Nothing that I can think of in terms of what I like least.

Overall experience is good. There are countless libraries that you can install and work with them to perform tasks related to your business domain.

We used Anaconda in one of the largest banks in Pakistan. We used R language to perform data analyses including data cleansing, data analyses and future predictions. It is very easy to use and you can install it in your personal computer without any hurdles. It also has a lot of libraries that you can install without any issues.

it has some errors while installing new packages like PyViz packages. Also if you open the Jupyter Lab in chrome browser, You will get error while downloading the files.

Good overall experience with Anaconda.

Managing virtual environments is very easy and effective with Anaconda. We can also specify the version of python to use while creating a new virtual environment.

There are no such features I do not like about this software.

Good experience

Anaconda is very easy to use python package manager. We can use jupyter notebooks, spyder and many other from anaconda navigator easily.

Anaconda navigator takes some time to load in my device.

Anaconda is a great platform as it has everything one needs to do Data Science and Machine Learning. It gives one access to Jupyter Notebook, R Studio, Orange, etc via the interface where you can choose what you need to install. Spyder is a good IDE which is included with the package. The individual edition is fee of cost while there are other paid SaaS versions for the enterprise. It also has all the important Python open-source tools one needs such as NumPy, Matplotlib and Panda, along with all the libraries you need to do your work. They also provide access to documentation for the various services in case you are stuck somewhere.

Sometimes there are issues if you need to do something and it doesn't work with the current version of Python and this causes some frustration. On rare occasions, there is a bit of a lag. Some of the services consume a lot of resources randomly.

Anaconda is a great software for python programming and I am impressed with the other scientific apps that come preinstalled in the IDE.

Package management/ installations and virtual environment creation are easier workarounds to get you started with python programming in Jupyter notebook.

I haven't encountered issues yet, it's good for now.

There are several programming tools available, and the library management system is quite robust, user-friendly, and intuitive. Release notes can be handled extremely nicely, and the community on this platform is really inviting.

As a result, I don't see anything wrong with an anaconda. Just that we are helpless when the kernal terminates, which happens from time to time.

Mostly using Anaconda for python coding in order to create data visualization that would not be possible on Excel.

First off, Anaconda is extremely easy to use for all your potential coding needs without downloading a lot of different software. Secondly, it's a strong platform to used for any python coding necessary for work.

None, I have had zero issues with this software since I started using it.

I used anaconda distribution platform for python. I used spyder and jupyter for academic purpose and they are very good with their interfaces and help features

Some of the pros of this software are large number of applications you can use. It has good environment features and can create multiple custom features. You can have multiple versions of same application. It has large base of applications amounting to ten thousand

It is a bit difficult to use at the beginning. Once you go through tutiorials it gets easy to use the app. To use an app which isn't in the package like pycharm, it needs some time to get used to it

Running scripts essential for carrying out our payment processes - this involves a highly complex function that integrates data from Metabase. This is run through Jupyter Notebook within Anaconda.

It's really well-integrated with our Metabase data - I can run a highly complex Python script through Jupyter Notebook within Anaconda to acquire data that would otherwise be hugely time-consuming to collect. I also like how it's integrated with IBM Watson Cloud Studio for better data visualisation.

It can be really slow to open Anaconda, and initially I was very confused about the different applications integrated into it as it's not immediately obvious what the difference between some of them is (e.g. Jupyter lab v Jupyter notebook), with the explanations not being that clear. To be honest I still don't know why my script only runs through Jupyter Notebook within Anaconda - and there doesn't seem to be an easy way to find out?

Very good interface to use other computer software and library such as spyder

It could be more user friendly in terms of user interface

Awesome! You have all you need to start coding in Python in just one tool.

This is a comprehensive tool if you want to start your journey as a Data Scientist. It not only install Python, as it also includes Jupiter app, so you will find all you need to start programming and extract more from your data.

The process of updating libraries could be improved to be more friendly, as you need some technical skills to manage that in the latest versions.

The tool allows you to easily create development environment for a particular version of python and install update libraries. Great tool to optimize time.

The application takes time to load and change development environment.

Great software, I have it saved in my tool bar and I use it often. Recommended.

Very nice and functional. I use it for python and the jupyter notebook works very well. It's my go-to software.

No issues identified. Through anaconda you have access to multiple softwares, if you already know you're not going to use some of them, it would be nice to remove them maybe.

It serves as a great IDE for a data developer, and all the libraries one could need are included.

Anaconda takes a lot of time to load up, it should load a bit quicker.

Being a beginner enjoying doing my data science projects with help of Anaconda

All data science project required libraries are available in anaconda , being beginner can use it very ease

As of now i like its a great platform, will update the same in future

In short: easy and productive. Endless possibilities and a programming shell that makes it easy to "learn by doing".

The shell reminds me of Matlab, which made my learning curve easier and faster. I can keep on eye at the values taken by (most) variables in my program and build up the code step by step, testing instructions and "seeing" results as they are stored in memory. Access to Pyhton's statistical and data-science functions is made easy.

It is hard to find drawbacks, but I may mention the fact that the huge number of functions available can make you feel lost at times. Also, context help is good, but can always be improved.

It was easy to use and it has support for multiple applications to make it easy to use multiple features from the same application.

Although it supports multiple applications it can be bulky, which in turn can make your code execution slow if you have a low end system

Good but it can be much better

Beginners guide to Python Default IDE for Python development Interactive GUI Wide variety of Libraries to choose from Free to use

Quite Outdated compared to newer IDEs Direct implementation on other OS Debugging difficult in Anaconda compared to Jupyter or Colab