Google Classroom vs. TensorFlow

Google Classroom allows teachers to post for daily lessons and assignments. It also allows teachers to be able to communicate with students easily outside of class. Students are able to stay connected and know where to find all information and resources easily in a streamlined manner for all of their classes.

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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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• Student-teacher communication - I love using Classroom for this because my students can always go back and check what was on Classroom by looking through the stream. This way they don't have to go dig through emails to find what they're looking for.
• Posting to multiple classes - I can post the same announcement or assignment to multiple classes at once without having to repeat the process or send separate emails.
• Streamlining grading - when students turn work in on Classroom, it all goes to one place and then when I'm grading I can open their documents directly from Classroom or my Drive folder. This way, I'm not looking through emails and Google Doc shared files for their assignment.

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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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• The content management of the Classroom is not that good. The sub-section for notes, syllabus, or discussion is missing.
• It doesn't have parental control feature.
• It converts the excel output into a normal file. All the formulas and pivots got changed into plain text.

• 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.

Testing is particularly important in online learning, and Google Classroom falls far short of other learning management systems in this regard. Security is also a concern: while account control is reasonable for the account used with Google Classroom, the person controlling a particular account is often able to, for example, forward or download proprietary materials.

Simple design and seamless integration with Google tools and drive, but missing some key features. However, since it is limited in overall functions and ability to truly personalize / customize, it is quite user friendly and easy to set up and get going, other than sending out the code to your course or dropping students in via their gmail account. Users of Google Forms and sites will find the layout similar in design.

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Support of multiple components and ease of development.

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We have had very little trouble in accessing Google Classroom. Our issues, if any, have risen from our server and not the Google servers.

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Since this platform is provided by Google, the technical support is better than any others, and we are not required to bother about the space constraints for adding the contents. If we have a good uninterrupted internet facility we can access Google Classroom without any delay or lag. They have app support in both Android and iPhone.

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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It was relatively easy to implement due to the simplicity of the platform. Even our more technology challenged teachers found it easy to get started with Google Classroom.

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Use of cloud for better execution power is recommended.

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I haven't tested or evaluated another digital classroom website or application. I feel like Google Classroom is convenient for many reasons such as compatibility to Google docs, slides, etc. I also love the ability to link to YouTube and other sites. I don't know if there would be a site that is easier to maneuver.

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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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It is very easy to push out this program across our buildings. Teachers are able to use it without much trouble.

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• Students are able to continue learning in a remote environment
• Parents have a single, consistent organization structure to make it easy to track assignments and progress for multiple children
• Much better solution than the quickly assembled Zoom-and-gloom of the previous spring when school abruptly went remote with no planning

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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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