Likelihood to Recommend A well-suited scenario for using AWS Tensor Flow is when having a project with a geographically dispersed team, a client overseas and large data to use for training. AWS Tensor Flow is less appropriate when working for clients in regions where it hasn't been allowed yet for use. Since smaller clients are in regions where AWS Tensor Flow hasn't been allowed for use, and those clients traditionally don't have enough hardware, this situation deters a wider use of the tool.
Read full review As a Data Analyst, it is my job to analyze large datasets using complex mathematical models. Anaconda provides a one-stop destination with tools like PyCharm, Jupyter, Spyder, and RStudio. One case where it is well suited is for someone who has just started his/her career in this field. The ability to install Anaconda requires zero to little skills and its UI is a lot easier for a beginner to try. On the other hand, for a professional, its ability to handle large data sets could be improved. From my experience, it has happened a lot that the system would crash with big files.
Read full review Pros Amazon Elastic Compute Cloud (EC2) allows resizable compute capacity in the cloud, providing the necessary elasticity to provide services for both, small and medium-sized businesses. Tensor Flow allows us to train our models much faster than in our on-premise equipment. Most of the pre-trained models are easy to adapt to our clients' needs. Read full review It provides easy access to software like Jupyter, Spyder, R and QT Console etc. Easy installation of Anaconda even without much technical knowledge. Easy to navigate through files in Jupyter and also to install new libraries. R Studio in Anaconda is easy to use for complex machine learning algorithms. Read full review Cons SageMaker isn't available in all regions. This is complicated for some clients overseas. For larger instances, when using a GPU, it takes a while to talk to a customer service representative to ask for a limit increase. Given this, it's recommendable to ask in advance for a limit increase in more expensive and larger cases; otherwise, SageMaker will set the limit to zero by default. Since the data has to be stored in S3 and copied to training, it doesn't allow to test and debug locally. Therefore, we have to wait a lot to check everything after every trail. Read full review Although I have generally had positive experiences with Anaconda, I have had trouble installing specific python libraries. I tried to remedy the solution by updating other packages, but in the end, things got really messed up, and I ended up having to uninstall and reinstall a total of about 4 times over the past 2 years. If you have the free version of Anaconda, there is not much support. Googling questions and error messages are helpful, but there were times when I wished I would have been able to ask technical support to help me troubleshoot issues. There were a few times when I tried to install tensorflow and tensorboard via Anaconda on a PC, but I could not get them to install properly. Anaconda allows you to create 'environments' , which allow you to install specific versions of python and associated libraries. You can keep your environments separate so they do not conflict with one another. Anyway, I ended up having to create several 'conda envrionments' just so I could use tensforflow/tensorboard and a few other utilities to avoid errors. This was somewhat annoying, because every time I wanted to run a specific model, I'd have to open up the specific conda environment with the appropriate python libraries. Read full review Likelihood to Renew It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.
Read full review Usability The interface is an easy to use command-line interface, or a GUI for launching and/or discovering different parts of the system.
Read full review Support Rating Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.
Read full review Alternatives Considered Microsoft Azure is better than Amazon Tensor Flow because it provides easier and pre-built capabilities such as Anomaly Detection, Recommendation, and Ranking. AWS is better than IBM Watson ML Studio because it has direct and prebuilt clustering capabilities AWS, like IBM Watson ML Studio, has powerful built-in algorithms, providing a stronger platform when comparing it with MS Azure ML Services and Google ML Engine.
Read full review ANACONDA VS
Alteryx Analytics : Even though I find Alteryx to be an excellent tool for managing extremely massive data, Anaconda is much better and easy for analytics. Anaconda VS.
MicroStrategy Analytics : Compared with Anaconda,
MicroStrategy Analytics is very difficult to use and counter-intuitive Anaconda VS.
Power BI For Office 365 : One of the main advantages of BI for Office 364 is its capacity to data connectivity. However, it's very hard to edit data connections, once BI for Office is deployed in other platforms
Read full review Return on Investment Positive: It has allowed us to work with our overseas teams without any large hardware investing. Positive: Pre-trained models significantly reduce the time to develop solutions for our clients. Negative: Since it's a relatively new tool, you have to be careful about not paying for large errors while learning to use the tool. Read full review Positive: Lower maintenance cost compared to other tools on the market Positive: Ease in hiring professionals already accustomed to the tool in the job market Positive: Projects are portable, allowing you to share projects with others and execute projects on different platforms, reducing deployment costs Read full review ScreenShots