TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.
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Yardi Voyager
Score8.7 out of 10
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Yardi Voyager provides residential and commercial property management software. Capabilities include integrated accounting, lease renewal workflow, and modules for multi-family, senior, and affordable housing, as well as retail, office and industrial units.
The company was founded in 1984 and has 4,000 employees and 35 offices around the world.
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).
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Yardi Voyager is best suited for users in the multifamily and commercial real estate space, and can be used across a wide range of employee roles, including management, leasing, maintenance, operations, asset management, ownership, and more. On the leasing side, Yardi Voyager is best paired with either Yardi CRM or Yardi CRM IQ (Yardi's newest feature program), as they bring a more robust CRM product that helps with managing prospects and residents. Yardi Voyager houses operations for the majority of integrations across a wide range of industries and vendors, and it comes highly recommended by those industries and vendors when it comes to use of APIs and cross functionality
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The out-of-box reports are comprehensive and dynamic, in that you can drill down into specific data columns to see more detail.
The setup of properties is simple and intuitive, and not that different from other multifamily software competitors, which helped with the transition.
The residential Manager dashboard hosts a great snapshot of the property management performance of a property in real-time. It is easy to locate current occupancy, leasing activity, and maintenance request data.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
In my experience there's a fairly steep learning curve for a new user to be able to navigate the system
While there's diverse functionality, many items seem buried in menus or obscure places, particularly the first time you're trying to find them
Getting used to the refresh functionality in some parts of the system can be challenging if you're used to a system that automatically updates when new filters are applied
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We have invested 5 years of setup, implementation and training on Voyager. It's doing a very good job for us and I feel we've only scratched the surface of its capabilities. Yardi support has been very responsive with very little down time. The training materials are great from Client Central
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Overall it is a reliable and relatively easy product to utilize. No Property Management Software is simple to implement, so a return on investment is delayed and care should be made to ensure that this platform does everything you need for it to do. Experience and knowledge in SQL programming language is helpful, as there are many SQL reports and scripts available to be able to better utilize the software. It takes time to find the ones useful and the ones that resolve hiccups.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The local office is very knowledgeable, however recently it seems that Yardi has begun to route calls offshore and the knowledge base there does not seem to be as strong as the USA based support centers. All customizations are done by offshore personnel, which presents issues in terms of the language barrier and time zone differences.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
If you are converting from another system, grouping your properties by subsidy type seemed to help us. We were able to focus on a half dozen properties at a time, rather than the entire portfolio.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Citrix and Argus are property management tools that each fill a function. Citrix is used to track real time payments, while Argus is used for modeling and cash flow analysis. Yardi combines many of the features between the two. Though it is more difficult to use, fully integrating Yardi into a company could save time and money and standardize many of the finance operations of Real Estate asset management firms.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Plugin in updates are a pain point. I think when Yardi has updates that they should have vetted it and that us the client shouldn't have to test thousands of plugins to see what is different. Just leaving the information on client central for the end user to look at, at their leisure is in my opinion not the best way to handle, you should send out updated white papers to the SPOCS to let them know what changes are coming.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
