External reviews
242 reviews
from
and
External reviews are not included in the AWS star rating for the product.
Anaconda Review
What do you like best about the product?
Anaconda is open-source and accessible to use for any machine learning, deep learning, data science problems using Python or R Programming Language on a single machine. It has tools and IDEs like Jupiter notebook, spyder, etc, that work with open-source packages and libraries.
There is Anaconda Navigator and Anaconda Command Prompt to work and create multiple environments with different versions of libraries and programming languages.
There is Anaconda Navigator and Anaconda Command Prompt to work and create multiple environments with different versions of libraries and programming languages.
What do you dislike about the product?
Anaconda has a few bugs that do not let a few libraries install and work efficiently.
Anaconda is slower than the independent python package.
Anaconda consumes more ram of machines sometimes that makes it not responding.
Anaconda is slower than the independent python package.
Anaconda consumes more ram of machines sometimes that makes it not responding.
What problems is the product solving and how is that benefiting you?
Anaconda software helps solve problems related to Machine Learning, Deep Learning, Data Science, Computer Vision, Geospatial Data Analysis & Modelling, Satellite Data Analysis, etc.
Anaconda can easily install and manage multiple external libraries in the environment using pip and conda install commands.
Anaconda can easily install and manage multiple external libraries in the environment using pip and conda install commands.
Recommendations to others considering the product:
Anaconda is very easy to use and can manage the libraries in the environment of different programming languages.
It has various training materials and tutorials which will be helpful for beginners to start with data science, machine learning-related problems.
It has various training materials and tutorials which will be helpful for beginners to start with data science, machine learning-related problems.
Best develpement environment for Machine Learning
What do you like best about the product?
1. Amazing set of features ease the development of any data science project.
2. We can use Jupyter Notebook to create .ipynb files and even use them on DataBricks.
3. Installing any library is pretty straightforward.
4. I use Spyder to run python scripts on my local computer.
2. We can use Jupyter Notebook to create .ipynb files and even use them on DataBricks.
3. Installing any library is pretty straightforward.
4. I use Spyder to run python scripts on my local computer.
What do you dislike about the product?
It uses a lot of RAM, which sometimes makes the laptop very slow. Sometimes version inconsistencies arise in libraries.
What problems is the product solving and how is that benefiting you?
I use it for Data Science, Machine Learning, and other analytics tasks. For writing python scripts for local computer.
Recommendations to others considering the product:
If you are a beginner, then start with Anaconda. Then you can move to other platforms like DataBricks for collaborative projects.
Seamlessly connect to apis for using the power of python for data analysis
What do you like best about the product?
Easy to install all the required packages/library for use of data analysis. Jupyter notebook can be used after installing this for writing python codes
What do you dislike about the product?
No point of dislike as such. Sometimes it is hard to add missing library.
What problems is the product solving and how is that benefiting you?
I am using anaconda to automate data integrity checks using a python code and connection to hive database
Recommendations to others considering the product:
Good tool for data analysis
Best IDE for the Data science project
What do you like best about the product?
- All data science tool is available in single umbrella.
-almost all required libraries have available in it.
- Easy to create a notebook for the data science project.
-Easy to work on multiple python environments based on your requirement.
- In community easy to find the forum/ events
-almost all required libraries have available in it.
- Easy to create a notebook for the data science project.
-Easy to work on multiple python environments based on your requirement.
- In community easy to find the forum/ events
What do you dislike about the product?
- Consuming more time to load the first time application.
-Sometimes it is stopped due to consumes more ram.
-Sometimes it is stopped due to consumes more ram.
What problems is the product solving and how is that benefiting you?
- It is used for creating the ML model
- Data analysis
- Data visualisation
- Creating the notebook for sharing the code and description.
- Data analysis
- Data visualisation
- Creating the notebook for sharing the code and description.
Recommendations to others considering the product:
I would recommend to data scientists can use it.
Best IDE for starters
What do you like best about the product?
Perfect for learning and programming, a lot of ready-to-use libraries are present. Version management is easy to control.
What do you dislike about the product?
It is heavy on resources and hence lags sometimes, an option to install only required packages would be excellent.
What problems is the product solving and how is that benefiting you?
I used anaconda platform for python programming and development
Anaconda Enterprise to program computer applications using interpreted languages
What do you like best about the product?
That the community version is free and that the creation of virtual environments is simple.
What do you dislike about the product?
That the documentation is not robust enough to walk you through the steps with no external aid.
What problems is the product solving and how is that benefiting you?
Machine Learning applications
Recommendations to others considering the product:
Follow online tutorial by other users
Found difficulties while installing Environments
What do you like best about the product?
Lots and lots of enviroments of python can be created with different libraries.
What do you dislike about the product?
Hard to install libraries sometimes using pyip and also with conda e.g. tensorflow-gpu after installing doesn’t relect on environment in jupyter notebook
What problems is the product solving and how is that benefiting you?
Great interface and all of things like jupyter notebook, spyder and CLI and all at same place for every environment.
Different set of tools for advance programmers
What do you like best about the product?
Anaconda enterprise is one among it's native different tools. It stood alone when we talk about data science. It has many softwares in it and also helps to fix there dependencies and integrated functionality without conflicting with there environments as anaconda creates a virtual for them that separates it from other tools of the system.
What do you dislike about the product?
Anaconda is one of the trending and most liked tool for data analysis because of it's complete set of small tools. But this makes it a bit bulky which requires heavy computation and is not compatible with old system.
Although it's not a big issue to discuss but it's libraries requires commands like pip to operate which makes me disappointing at some level.
Although it's not a big issue to discuss but it's libraries requires commands like pip to operate which makes me disappointing at some level.
What problems is the product solving and how is that benefiting you?
Anaconda comprises of many data analysis and data science tools which is a fascinating way to complete your work. Working in the data science internship projects I mostly preferred anaconda because of it's unique environment that it provides to run different softwares on the system and for the dependencies that it distinguished with on it's own. We don't always need to install different version of python for different libraries and tools, anaconda takes care of all about it. It helped me in completing my every goal with some good results and impressive impression on the viewers faces.
Recommendations to others considering the product:
Anaconda is a complete libraries of tools in itself. All those who wants to sharpen there skills can connect to anaconda community in order to grow more.
An essential tool for Data Science
What do you like best about the product?
Simple integration of Jupyter notebooks for EDA and prototyping, Spyder for writing more complex scripts and ease of package management. RStudio is a nice added bonus too.
What do you dislike about the product?
Prone to bugs when you're maintaining multiple envs and package versions. Hangs while updating.
What problems is the product solving and how is that benefiting you?
Solving NLP problems using Jupyter, experimenting with new approaches to advance our current offering.
Anaconda: Python in a bag
What do you like best about the product?
Easy to deploy, vast community that can offer support and very easy to create environments.
What do you dislike about the product?
Does not always allow you to stay up to date with modules or particular GitHub installations. Size can be an issue.
What problems is the product solving and how is that benefiting you?
Scientific computing and intensive statistical computation
Recommendations to others considering the product:
Your experience with anaconda can be the most useful If you are not planning on using free modules or extras available on the internet.
showing 101 - 110