Books on time series and sequence classificationTime series classificationUsing RNN (LSTM) for predicting one future value of a time seriesRNN time-series predictions with multiple features containing non-numeric features and numeric features?Why are RNN/LSTM preferred in time series analysis and not other NN?Time Series prediction using LSTMs: Importance of making time series stationaryLSTM for time series forecasting with H20.aiKeras LSTM with 1D time seriesTime series pixel classificationBinary classification model with time series as variablesInput shape for simpler time series in LSTM+CNN
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Books on time series and sequence classification
Time series classificationUsing RNN (LSTM) for predicting one future value of a time seriesRNN time-series predictions with multiple features containing non-numeric features and numeric features?Why are RNN/LSTM preferred in time series analysis and not other NN?Time Series prediction using LSTMs: Importance of making time series stationaryLSTM for time series forecasting with H20.aiKeras LSTM with 1D time seriesTime series pixel classificationBinary classification model with time series as variablesInput shape for simpler time series in LSTM+CNN
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Though I have been using traditional machine learning algorithms (Regression and Classification) , I have no experience of using Time series and would like to understand what is time series and different approaches(ex:ARIMA,SARIMA,SARIMAX, LSTM etc) used for time series analysis. I also see that people use LSTM's/RNN for time series/sequence classification. Can you people recommend me a book that discusses the above algorithms and how Time series is different from sequence classification etc?
machine-learning deep-learning time-series lstm books
edited yesterday
Media
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asked yesterday
SELVASELVA
211
$endgroup$
add a comment |
$begingroup$
Though I have been using traditional machine learning algorithms (Regression and Classification) , I have no experience of using Time series and would like to understand what is time series and different approaches(ex:ARIMA,SARIMA,SARIMAX, LSTM etc) used for time series analysis. I also see that people use LSTM's/RNN for time series/sequence classification. Can you people recommend me a book that discusses the above algorithms and how Time series is different from sequence classification etc?
machine-learning deep-learning time-series lstm books
edited yesterday
Media
7,36562161
asked yesterday
SELVASELVA
211
$endgroup$
add a comment |
$begingroup$
Though I have been using traditional machine learning algorithms (Regression and Classification) , I have no experience of using Time series and would like to understand what is time series and different approaches(ex:ARIMA,SARIMA,SARIMAX, LSTM etc) used for time series analysis. I also see that people use LSTM's/RNN for time series/sequence classification. Can you people recommend me a book that discusses the above algorithms and how Time series is different from sequence classification etc?
machine-learning deep-learning time-series lstm books
edited yesterday
Media
7,36562161
asked yesterday
SELVASELVA
211
$endgroup$
Though I have been using traditional machine learning algorithms (Regression and Classification) , I have no experience of using Time series and would like to understand what is time series and different approaches(ex:ARIMA,SARIMA,SARIMAX, LSTM etc) used for time series analysis. I also see that people use LSTM's/RNN for time series/sequence classification. Can you people recommend me a book that discusses the above algorithms and how Time series is different from sequence classification etc?
machine-learning deep-learning time-series lstm books
machine-learning deep-learning time-series lstm books
edited yesterday
Media
7,36562161
asked yesterday
SELVASELVA
211
edited yesterday
Media
7,36562161
asked yesterday
SELVASELVA
211
edited yesterday
Media
7,36562161
edited yesterday
Media
7,36562161
edited yesterday
Media
7,36562161
7,36562161
asked yesterday
SELVASELVA
211
asked yesterday
SELVASELVA
211
asked yesterday
SELVASELVA
211
211
add a comment |
add a comment |
1 Answer
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$begingroup$
There are numerous topics that you've mentioned but I will suggest those which I've read and are helpful.
For hidden markov models and markov processes I suggest reading Pattern Classification by Richard O. Duda. You can also take a look at Pattern Recognition and Machine Learning by Christopher Bishop. For better understanding Markov processes and their behaviour, you can also take the course stochastic process which is also known as random process. I suggest taking that course before reading any book, because you may need some help if you're not very familiar to the concepts.
For LSTMs, I highly suggest taking a look at the fifth course of deep learning on coursera by pr. Andrew Ng. If you do their homework you can realise how the inner operations exactly work and you'll have a very deep understanding of time series and what their nature is. After that, you can take a look at the Deep Learning book by Ian Goodfellow.
answered yesterday
MediaMedia
7,36562161
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$begingroup$
There are numerous topics that you've mentioned but I will suggest those which I've read and are helpful.
For hidden markov models and markov processes I suggest reading Pattern Classification by Richard O. Duda. You can also take a look at Pattern Recognition and Machine Learning by Christopher Bishop. For better understanding Markov processes and their behaviour, you can also take the course stochastic process which is also known as random process. I suggest taking that course before reading any book, because you may need some help if you're not very familiar to the concepts.
For LSTMs, I highly suggest taking a look at the fifth course of deep learning on coursera by pr. Andrew Ng. If you do their homework you can realise how the inner operations exactly work and you'll have a very deep understanding of time series and what their nature is. After that, you can take a look at the Deep Learning book by Ian Goodfellow.
answered yesterday
MediaMedia
7,36562161
$endgroup$
add a comment |
$begingroup$
There are numerous topics that you've mentioned but I will suggest those which I've read and are helpful.
For hidden markov models and markov processes I suggest reading Pattern Classification by Richard O. Duda. You can also take a look at Pattern Recognition and Machine Learning by Christopher Bishop. For better understanding Markov processes and their behaviour, you can also take the course stochastic process which is also known as random process. I suggest taking that course before reading any book, because you may need some help if you're not very familiar to the concepts.
For LSTMs, I highly suggest taking a look at the fifth course of deep learning on coursera by pr. Andrew Ng. If you do their homework you can realise how the inner operations exactly work and you'll have a very deep understanding of time series and what their nature is. After that, you can take a look at the Deep Learning book by Ian Goodfellow.
answered yesterday
MediaMedia
7,36562161
$endgroup$
add a comment |
$begingroup$
There are numerous topics that you've mentioned but I will suggest those which I've read and are helpful.
For hidden markov models and markov processes I suggest reading Pattern Classification by Richard O. Duda. You can also take a look at Pattern Recognition and Machine Learning by Christopher Bishop. For better understanding Markov processes and their behaviour, you can also take the course stochastic process which is also known as random process. I suggest taking that course before reading any book, because you may need some help if you're not very familiar to the concepts.
For LSTMs, I highly suggest taking a look at the fifth course of deep learning on coursera by pr. Andrew Ng. If you do their homework you can realise how the inner operations exactly work and you'll have a very deep understanding of time series and what their nature is. After that, you can take a look at the Deep Learning book by Ian Goodfellow.
answered yesterday
MediaMedia
7,36562161
$endgroup$
There are numerous topics that you've mentioned but I will suggest those which I've read and are helpful.
For hidden markov models and markov processes I suggest reading Pattern Classification by Richard O. Duda. You can also take a look at Pattern Recognition and Machine Learning by Christopher Bishop. For better understanding Markov processes and their behaviour, you can also take the course stochastic process which is also known as random process. I suggest taking that course before reading any book, because you may need some help if you're not very familiar to the concepts.
For LSTMs, I highly suggest taking a look at the fifth course of deep learning on coursera by pr. Andrew Ng. If you do their homework you can realise how the inner operations exactly work and you'll have a very deep understanding of time series and what their nature is. After that, you can take a look at the Deep Learning book by Ian Goodfellow.
answered yesterday
MediaMedia
7,36562161
answered yesterday
MediaMedia
7,36562161
answered yesterday
MediaMedia
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answered yesterday
MediaMedia
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