Amazon Deep Learning AMIs vs. Tableau Public

Amazon AMIs has been very useful for the quick setup and implementation of deep learning for data analysis which is something I have used the service for in my own research. We commonly use the service to enable students to run intensive deep learning algorithms for their assessments. This service works well in this scenario as it allows students to quickly set up a suitable environment and get started with little hassle. If you are looking to run simple, surface level deep learning algorithms (kind of contradictory statement I know) then AMI is more complicated than most will need. When it comes to teaching the basics of Machine Learning, this kind of system is unnecessary and there are other alternatives which can be used. That being said this service is a must if you are looking to run complex deep learning via the cloud.

Incentivized

Tableau public is the best platform to build dashboards for your personal profile and share with recruiters. It's always good to keep ourselves updated on the latest features, create sample dashboards and save them to a personal profile. Tableau public is free and doesn't need any subscription. anyone can create an account and start building reports.

• Setting up environment
• Support for different types of machines
• Perfect for Machine Learning / Deep Learning use cases
• Nvidia / Cuda / Conda support easily

Incentivized

• Data visualization: lots of different options, including bar, scatter, pie, waterfall charts to explore relationships between variables, and to present findings/trends to different teams
• Integrates readily with limited, though different data sources: TXT, CSV, TDE, Access
• Exports reports for review of different dashboards: client-ready/team-ready, with a clean and tidy presentation in PDF format (or hardcopy)

Incentivized

• Some aspects of the User Interface are quite confusing and activating packages can be a bit convoluted
• It can be a bit confusing to switch between frameworks for novice users

Incentivized

• Tableau Public (both Desktop and Server) like their "for a fee" counterparts offer very easy to learn and use tools to transform data into pictures and gain insights into your data. Most organizations report a reduction in development time of 10x vs. other similar tools, due to the intuitive user interface. That said, with Tableau Public, published workbooks are "disconnected" from the underlying data sources and require periodic updates when the data changes. Users are limited to 1 Gb of storage space per user ID and password as well.
• I would like to see better options for public sharing of visualizations and data from within the "for a fee" products as more and more organizations are moving in the direction of data sharing with partners and their communities.

Incentivized

It's free, right? I'll keep using the free version. So the real question to ask is this? Will I pay $999 for the Personal version or $1,999 for the Professional? Yikes! That is a big stretch. I'm not sure about that. The product comparison chart is at: http://www.tableausoftware.com/public/comparison

Tableau public is a great training tool to understand the basics of Tableau before buying it. A great tool to extend Excel's visualization and to publish data for others. Not useful for anything you need secure. No ability to access databases. Static information only.

I have not yet required to contact support as the documentation and help i found online has always worked so far

Incentivized

I found it sufficient, and fast. I could easily "kick the tires" with Tableau on my data so I got up and running fast.

Start at the end and work backward. Identify the business case / issue and questions the end users have, then identify the data needed, and where to get it.

Incentivized

Both of these services provide similar functionality and from my experience both are top class services which cover most of your needs. I think ultimately it comes down to what you need each service for. For example Amazon DL AMIs allows for clustering by default meaning I am able to run several clustering algorithms without a problem whereas IBM Watson Studio doesn't provide this functionality. They both provide a wide range of default packages such as Amazon providing caffe-2 and IBM providing sci-kitlearn. My main point is that both are very good services which have very similar functionality, you just need to think about the costs, suitability of features and integration with other services you are using.

Incentivized

Google Charts/Drive is sufficient for simpler data sets, but it does not integrate with other web platforms and the visualization does not look as professional. I'm not aware of any other competitors that offer the same package as Microsoft.

Incentivized

• Saves a lot of Infra Costs
• Saves a lot of time in handling environment issues
• Easy to start a new instance

Incentivized

• Tableau Public visualizations have helped drive traffic to our content and sites
• The lack of cost means it's easy to demonstrate our experience to attract paying clients

Incentivized