Amazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
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e-automate
Score 8.2 out of 10
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ECI Software Solutions offers e-automate, an ERP for office technology companies to automate business workflows and increase contract profitability.
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TensorFlow
Score 7.7 out of 10
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TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.
It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.
If you need a system to place and track sales quotes, sales orders, purchase orders, and service calls then E-Automate is perfect. However, if you want to be able to easily bulk upload customers and contracts or if you want to be able to quickly and easily track contract profitability, customer costs, etc, then you'll likely want/need a secondary or different system to do so.
TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
Sending Invoices out to customers via email or printing.
Keep track of ordering and inventory.
Sales Tax reporting.
Monitoring customer payment activity/setting up and removing credit holds.
Calculating payments to process each cycle.
Excellent aging reports.
I like the fact that when I am looking at one item, such as an invoice, I have the capability to switch to the customer menu rather than having to exit out of invoices and then enter into customers.
I love the flexibility of the search menus - being able to sort on several factors at once.
It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
Make sales invoices not require serial numbers, or be more flexible with it.
Make contract invoices have some sort of flexibility in terms of editing. Our end users complain that QuickBooks made it very easy to edit invoices, and in e-automate, for them, it is practically impossible. (I do personally understand why it has to be as it is myself, I'm just forwarding their observation.)
Make the API actually useful. I spent days looking at the functions and the functions available are not really useful.
Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
Its really the only option for the industry that does enough of what we need for it to function . I'm not sure if there were better options out there if we would have to renew our subscription. With the addition of AI, hopefully something will be able to become more useful.
The user interface may be slightly outdated, but it is very intuitive and easy to navigate. Once you have learned one module within the system it is very easy to apply that knowledge to any other module. It makes using the system much easier, and it makes training another person on the system quick and efficient.
Reports are the struggle the most with the information being extracted in a way that you need to copy and paste it into a new document so some of the information is not covered
Sometimes when you need answers quickly, a voice on the phone is far better than having to wait for email support or a callback. I have found this to have delays and feel ECI e-automate should invest more in its support infrastructure.
Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
E-automate is much better at understanding the needs of the office equipment industry and provide the necessary tools. SAP Business One has limited features specific to the office equipment industry and includes things that are not useful. E-automate is also priced much better and provides the best value for your investment.
Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
The e-automate will stop working if we stop paying each year. We chose not to go to the cloud and buy the software. QuickBooks and other software are a one-time fee.
E-automate has very few outside vendors for add-on modules.
