[GitHub] indhub opened a new issue #6493: Tutorials that need improvement

[GitBox <gi...@apache.org>]

indhub opened a new issue #6493: Tutorials that need improvement
URL: https://github.com/apache/incubator-mxnet/issues/6493
 
 
   Here is the list of tutorials that were removed from the website for not meeting the quality bar. These tutorials should be improved, reviewed and committed.
   
   - [How do I work with MXNet within a Matlab environment?](https://github.com/dmlc/mxnet/tree/master/matlab)
   - [Can I run MXNet in a browser using JavaScript?](https://github.com/dmlc/mxnet.js/)
   - [Object Detection using Faster R-CNN](https://github.com/dmlc/mxnet/tree/master/example/rcnn)
   - [Object Detection using SSD](https://github.com/dmlc/mxnet/tree/master/example/ssd)
   - [Neural Art - Transfer the style of one image onto the content the content of another image](https://github.com/dmlc/mxnet/tree/master/example/neural-style)
   - [Large Scale Image Classification](https://github.com/dmlc/mxnet/tree/master/example/image-classification)
   
   ### Natural Language Processing
   - [Text Classification using Convolutional Neural Networks](http://mxnet.io/tutorials/nlp/cnn.html)
   - [NCE Loss - Speed up text classification with large output layers](http://mxnet.io/tutorials/nlp/nce_loss.html)
   
   ### Speech Recognition
   - [Phoneme Classification - Use LSTM recurrent nets to recognize phonemes in audio](http://mxnet.io/tutorials/speech_recognition/speech_lstm.html)
   - [Baidu Warp CTC - Jointly learn predictions and alignments with CTC loss](http://mxnet.io/tutorials/speech_recognition/baidu_warp_ctc.html)
   
   ### Unsupervised Learning and Generative Modeling
   
   - [Generative Adversarial Networks](http://mxnet.io/tutorials/unsupervised_learning/gan.html)
   
   - [Autoencoders - Find low dimensional representations of data](http://mxnet.io/tutorials/unsupervised_learning/auto_encoders.html)
   
   - [Matrix Factorization - Discover latent factors of user preference in MovieLens data](http://mxnet.io/tutorials/python/matrix_factorization.html)
   
   - [Recommender Systems - Build a complete recommender system with matrix factorization](http://mxnet.io/tutorials/general_ml/recommendation_systems.html)
   
   ### R
   
   - [Neural Networks with MXNet in Five Minutes](http://mxnet.io/tutorials/r/fiveMinutesNeuralNetwork.html)
   
   - [Classifying Handwritten Digits with Convolutional Neural Networks](http://mxnet.io/tutorials/r/mnistCompetition.html)
   
   - [Classify Real-world Images with a Pre-trained Model](http://mxnet.io/tutorials/r/classifyRealImageWithPretrainedModel.html)	
   
   - [Dogs vs. Cats Classification with Fine-tuning](https://statist-bhfz.github.io/cats_dogs_finetune)
   
   - [Character-Level Language Modeling with LSTM RNNs](http://mxnet.io/tutorials/r/charRnnModel.html)
   
   ### Scala
   
   - [Create MXNet Scala Applications with the IntelliJ IDE](http://mxnet.io/tutorials/scala/mxnet_scala_on_intellij.html)
   
   - [Handwritten Digit Classification with Multilayer Perceptrons](http://mxnet.io/tutorials/scala/mnist.html)
   
   - [Character-Level Language Modeling with LSTM RNNs](http://mxnet.io/tutorials/scala/char_lstm.html)
   
   ### C++
   
   - [Basics](http://mxnet.io/tutorials/c++/basics.html)		
   
   ### Perl		
   
   - [Calculator, handwritten digits and roboshakespreare](http://blogs.perl.org/users/sergey_kolychev/2017/04/machine-learning-in-perl-part2-a-calculator-handwritten-digits-and-roboshakespeare.html)

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