Open LMS vs. TensorFlow

I currently use, talk about and promote all educators using Moodlerooms. The functionality that Moodlerooms provides is unmatched in most software. It is well suited in all educational realms. Teachers that teach all online electronic courses could use this to post assignments online, separate the classes and post a variety of assignments, tasks, and activities. Additionally, in blended situations where some students are face to face and sometimes working at home, the Moodlerooms makes it easy to education and be a hands-on teacher and a hands-on learner. Less appropriately, I find using Moodlerooms in some of the private sector industries could be tougher. Moodlerooms provides people and content management, and to use it in advertising or marketing and accounting, it could be difficult to find an easy use and function for it.

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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).

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• Something that Moddlerooms does very well is that it allows teachers to structure their online classroom as one focused curriculum.
• Moodlerooms also allows for customization of the layout. Being able to add and remove certain functions that Moodlerooms can perform definitely helps.
• Moodlerooms is able to add different types of activities to the rooms for increased interaction.
• Moodlerooms provides large chat opportunities to all students that are online at the same time.

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• A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
• Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
• Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.

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• Easier to change permissions.
• Adding the ability to tweet.
• Decrease bandwidth to improve back end loading times.

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• RNNs are still a bit lacking, compared to Theano.
• Cannot handle sequence inputs
• 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.

Support of multiple components and ease of development.

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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.

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Use of cloud for better execution power is recommended.

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I would select Moodlerooms over many competitors as a result of what it offers in terms of functionality and control. Google classrooms has a definite place in education; however, Moodlerooms provides significantly more control for authors. As the owner and manager of the content, and as someone familiar with technology, I can incorporate a lot more functions and create different layouts with functionality boxes

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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

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• Moodlerooms has given classes of mine a positive ROI because it improves the educational experience for all students. It has helped all of our students, and with this, we can even help students who can not get to the classroom for some reason.
• It helps to improve student scores, GPAs, and college attendance.
• The positive impact can be directly correlated with the improvement of grades for students. Being able to access work in person and via Moodlerooms helps students to learn anywhere and any time. Grades have improved, and that is due to Moodlerooms.

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• Learning is s bit difficult takes lot of time.
• Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
• Once you have learned this, it make your job very easy of getting the good result.

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