New answers tagged deep-learning
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How to add multiple embeddings (layers) to LSTM layer
Let's consider the main approaches:
Embed each categorical feature, then LSTM on top. I think you want to opt for individual recurrent layers when the features are sort of mutually exclusive, i.e. ...
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more insights about Word2Vec implementation
Bag of words(BOW) is a term generally used for the assumption where one doesn"t care about the order of the words. Words are usually treated as a ...
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Appropriate input size for nn.Embedding
nn.embedding layer is a sytactic sugar equivalent to one hot vector+ linear layer.
Suppose you have 2 distinct variables. and you want your model to learn their ...
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Dealing with varying predictive horizon
My understanding of your sample data is that you have X1, X2 as predictors, and two things you want to predict: whether target will be 0 or 1, and how many months before that result happens.
So, one ...
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What is the relationship between the accuracy and the loss in deep learning?
Ayúdenme a aclarar esta duda por favor
Después de ver este comentario:
------si sus datos están entre 0 y 1, una pérdida de 0,5 es enorme, pero si sus datos están entre 0 y 255, un error de 0,5 es ...
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What Deep Learning model to use in this spectroscopy task?
I think you need a deep learning model that can perform both image segmentation and image classification. Image segmentation is the process of dividing an image into regions or pixels that share some ...
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Why does cost function on a neural network increase?
I had similar problems and for me the reason was that my regularization parameter lambda was too high. I removed regularization completely and set it to 0 (that would be a good starting point). I was ...
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Build a topic model without data?
Yes, you certainly can, but understand that this would be a first step to getting your model off the ground and then later on you can refine the predictions and retrain the model to make it better. ...
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Prediction interval around LSTM time series forecast
You can easily quantify uncertainty for time series models using conformal prediction
https://github.com/valeman/awesome-conformal-prediction
Here is an article about doing it with classical models
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Why my validation loss and accuracy decays over epochs?
You are experiencing a lot of overfitting on the training set here.
I would go back and see if there are any inherent issues with the data (scaling? class imbalance? etc.) before diving into modeling.
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LMM Fine Tuning - Supervised Fine Tuning Trainer (SFTTrainer) vs transformers Trainer
The short answer is that a Supervised Fine Tuning Trainer (SFTTrainer) is used for Instruct Fine Tuning. The HuggingFace library SFTTrainer has also support for training with QLoRA (4-bit Quantised ...
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