New answers tagged deep-learning
0
votes
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. ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
0
votes
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 ...
1
vote
Accepted
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. ...
0
votes
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
...
3
votes
Accepted
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.
...
0
votes
Accepted
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 ...
Top 50 recent answers are included
Related Tags
deep-learning × 4834machine-learning × 1980
neural-network × 1413
keras × 807
tensorflow × 674
python × 572
cnn × 510
nlp × 422
lstm × 309
classification × 303
convolutional-neural-network × 286
computer-vision × 266
image-classification × 211
rnn × 194
time-series × 190
pytorch × 184
reinforcement-learning × 125
dataset × 119
transformer × 119
convolution × 118
training × 112
object-detection × 111
regression × 107
loss-function × 106
machine-learning-model × 101