The only way for Tom to prove his innocence is to reveal his true identity, something he has sworn not to do to protect the young woman he loves. A young woman who is on her way to New York. But after he is expelled he gets caught up in an international incident that could put his life in jeopardy. Emma fights for control of the family firm, the Barrington Shipping Company, while their daughter becomes engaged to a fellow art school student.
Both families look forward to the wedding, until a face from the past pays a visit. Meanwhile, Harry campaigns for the release of author Anatoly Babakov who has been imprisoned in Siberia, and may put his life in danger in the process. They don't all see eye to eye, of course. Then there's the mysterious Terror cat to contend with. Ultimately, though, To Be a Cat is a book about being comfortable in your own skin rather than someone else's fur. On the back, beneath a Eadweard Muybridge -style sequence of a black cat in motion, is the single line: "Be careful what you wish for …" As Lloyd Grossman used to say, let's look at the evidence.
Topics Children and teenagers. Fiction Children's books: years reviews. Reuse this content. Order by newest oldest recommendations. Show 25 25 50 All. Threads collapsed expanded unthreaded. Loading comments… Trouble loading? Hi Jason, I was using your code to solve a regression problem. I have the data defined exactly like you have but instead of casting them to one-hot-vectors I wish to leave them integers or floats.
Could you please suggest some solution. Much thanks! Hello Khan, I have a similar proble the network not predicting more than one step ahead. I just have a little AI and ML theory. Clearly, y specified by X reserve and subset. Thanks you! Not sure I follow. I am working on a water inflow forecast problem. I have access to weather predictions and I want to predict the water inflow, given the historical values of both weather and inflows. I have tried a simple LSTM model with overlapping sequences time series to supervised , taking weather predictions and past inflows as input, and outputting future inflows.
This works pretty well. Seeing all this Seq2Seq time series forecast trend, I have also tried it, by encoding the weather forecast and decoding them to water inflow with past inflows as decoder inputs , expecting even better results. But this Seq2Seq model is performing very poorly. Do you have an idea why? Should I give up this kind of models for my problem? I have read couple of your blogs about seq2seq and lstm. Wondering how should I combine this encoder-decoder model with attention? My scenario is kind of translation. You can do a greedy search through the predicted probabilities to get the most likely word at each step, but it does not mean that it is the best sequence.
Before you input the sequence, you need to reshape the sequences to 3D and best to train the model in mini batches as it will reset the states after every iteration which works really well for LSTM based model. Can this model be used to summarize the sentence? Am working on abstractive summarizer and trying to build one using encoder decoder with attention. Thank you for the great tutorial!! Not quite, it is because we defined a very large number of random examples that acted like a proxy for epochs. Hi Jason, nice post as always, I enjoy reading your blog.
I got on question here. I might missed something, but why do we need the shifted target sequence as input for the decoder? Would be nice if you can clearify that for me. Hi Jason, Thank you very much for your blog and its excellent content. Can we put an auto-decoder on top of it to reproduce the input1? Would this help the network in predicting the sequences? Bests Mostafa. Hi Jason, Thanks for the tutorial! Do you have any idea how I can do it? Also batch norm and dropout can interact, be careful not to use them side by side — always test.
Thank you so much for your exciting blog. What if we have more than one input series that are related to each other and want to predict the result? For example, predicting the weather which we have more than one features and series? I have many users belonging to one of the category and each user has visited some locations. Given a sequence of some user, I want to predict on which location that user will go next. The question is, how can we use the above post for the stated problem since in the post, the values are predicted in reverse order only.
Perhaps there are multiple ways to frame the problem. It sounds like a time series classification problem. Jason, while giving free tips, mind that code should be working in the real world for large datasets. One has to go to other places for a solution. BTW, your posts are intuitive. Can you please let me know the exact difference between both of these?
I generally teach an approach to the encoder-decoder that uses an autoencoder architecture as it often gives the same or better results as the more advanced encoder-decoder. What if I add validation split during fitting, would the model use teacher forcing during validation phase as well? Would this choice be correct, or should the model use greedy or beam search during the validation to simulate a more realistic performance?
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Tweet Share Share. Input1: ['1', '2', '3']. Source, Target [13, 28, 18, 7, 9, 5] [18, 28, 13] [29, 44, 38, 15, 26, 22] [38, 44, 29] [27, 40, 31, 29, 32, 1] [31, 40, 27] Source, Target. Accuracy: Alex November 2, at pm. Is this model suited for sequence regression too? For example the shampoo sales problem Reply. Jason Brownlee November 3, at am. Teimour November 2, at pm. Dk January 17, at pm. Hi, maybe this time you got any idea of multi-layer of LSTM autoencoder? Jason Brownlee January 18, at am.
James Wanga February 21, at pm. Kyu November 3, at am. How can I extract the bottleneck layer to extract the important features with sequence data? Thabet November 3, at am.
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Thank you Jason! Harry Garrison November 18, at am. I am facing an issue, though: I tried to execute your code as is copy-pasted it , but it throws an error: Using TensorFlow backend. What could have possibly gone wrong?
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Jason Brownlee November 18, at am. Perhaps confirm that you have the most recent version of Keras and TensorFlow installed. Carolyn December 8, at pm. Jason Brownlee December 8, at pm. Carolyn December 9, at am. Jason Brownlee December 9, at am. Thanks for sharing. Perhaps confirm that you have updated Keras to 2. George Orfanidis February 14, at pm. Thabet November 26, at am. Are the encoder-decoder networks suitable for time series classification? Jason Brownlee November 27, at am.
Jason Brownlee September 20, at am. Python November 30, at pm. Jason Brownlee December 2, at am. Pritish Yuvraj December 7, at am.
Jason Brownlee December 7, at am. Why would we have a word embedding at the output layer? Uthman Apatira March 2, at pm. Jason Brownlee March 3, at am. Joe May 25, at am. Is there such a tutorial yet? Sounds interesting. Jason Brownlee May 25, at am. Ashima March 30, at am. Hi Jason, I am trying to put embedding layer at encoder and decoder input with dense layer as it as you mentioned in the above code.
Jason Brownlee March 30, at am. I cannot debug your changes, sorry. Perhaps post your code and error to stackoverflow? Ashima April 5, at am. Could you please guide. Jason Brownlee April 5, at am. Not sure off the cuff, I think you will need to experiment. Dinter December 13, at am. Jason Brownlee December 13, at am. Dipesh January 11, at am. Jason Brownlee January 12, at am.
Dipesh Gautam January 17, at am. Any idea to add dropout? Jason Brownlee January 17, at am. Huzefa Calcuttawala January 23, at pm. Alfredo January 24, at pm. I look forward to hearing from you soon. Thanks Reply. Jason Brownlee January 25, at am. Dat February 22, at pm.
Thank you. Jason Brownlee February 23, at am. Return sequences does not return the hidden state, but instead the outcome from each time step. Liebman March 3, at am. Perhaps the data does not match the model, you could change one or the other. Liebman March 4, at am.
Jia Yee March 16, at pm. Dear Jason, Do you think that this algorithm works for weather prediction? For example, by having the input integer variables as dew point, humidity, and temperature, to predict rainfall as output Reply. Jason Brownlee March 16, at pm.
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Only for demonstration purposes. Lukas March 20, at pm. Hi Jason. Thank you Reply. Jason Brownlee March 21, at am. Jugal March 31, at pm. How to add bidirectional layer in encoder decoder architecture? Jason Brownlee April 1, at am. Use it directly on the encoder or decoder.
Luke April 3, at pm. Fatemeh August 8, at am. Hello, I also have the same issue. Sunil April 4, at am. Can you help me what could be the reason? It suggests the model has not learned the problem. Phetsa Ndlangamandla April 9, at pm. Hi Jason, In your current setup, how would you add a pre-trained embedding matrix, like glove? Jason Brownlee April 10, at am.
Lukas April 11, at am. Hi, Could you help me with my problem?
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Jason Brownlee April 11, at am. Lukas April 13, at pm. Jason Brownlee April 14, at am. Jameshwart Lopez April 17, at am. Im also not clear if this is a classification type of model. Can you please confirm. Jason Brownlee April 17, at pm.
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Kadirou April 17, at pm. Claudiu April 23, at pm. I have the same problem.. Did you solve it? Gary April 30, at am.