Questions tagged [machine-learning]
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.
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Does it make sense to have object detection model followed by a classification model
So i was working with the SKU110k dataset and i was required to identify the different items in the shelf as well but the SKU110k dataset only annotated shelf items but did not identify them. So i ...
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Is it appropriate to utilize LSTMs for multivariate binary prediction on a timeseries by sliding block-by-block vs row-by-row?
I am trying to implement an ML algorithm for multivariate regression on a list of several timeseries. There are hundreds of timeseries, each one millions of rows long. There are 13 features, and I'm ...
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NER with custom tags and no training data, zero shot approach help
I am building a "field tagger" for documents. Basically, a document, in my case something like a proposal or sales quote, would have a bunch of entities scattered throughout it, and we want ...
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Is there a way to create a bootstrapped beta calibration function to use on new data?
I have created ML classification models that are now to be evaluated on a different population for external validation (n=5000, event rates between n=400 and n=1200 for different outcomes under study)....
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LR not decaying for pytorch AdamW even after hundreds of epochs
I have following code using AdamW optimizer from pytorch:
optimizer = AdamW(params=self.model.parameters(), lr=0.00005)
I tried ...
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Using LSTMs for Predicting Targets with Known Feature Vector
I am trying to use an LSTM to predict the consecutive "offset" calibration values for an instrument. These offset values have previously been shown to be well correlated with a pair of ...
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Andrew Ng ML course using MATLAB?
Nowadays python is mostly used for machine learning and i think it is also used in new ML courses of Andrew Ng
https://www.quora.com/Why-was-MATLAB-not-used-in-the-Andrew-Ng-course-of-deep-learning
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Machine Learning vs Deep Learning? in context of Generative AI vs Discrimative AI?
I know that deep learning is subset of Machine learning
But is it correct that classical machine Learning algorithms mainly focus on implementing Discriminative AI while Deep learning algorithms ...
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hacky backprop outperforms clean backprop - Why?
I implemented a basic NN for MNIST in Numpy and started with a hacky implementation of backprop (just randomly multiplying gradients together), but somehow that one works better than my cleaned up ...
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Tuning NonHyperparameters in Scikitlearn
In Scikit Learn RandomSearch or GridSearch , how to include non hyper parameters in the tuning process?! Non hyper parameters are parameters not related to the machine learning algorithms. For example ...
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How does one handle a dataset with groups of features and groups of labels in classification?
I have a large dataset (1.8mil samples). There are 15 features: x1, y1, z1, e1, d1, x2,..., d3. (x,y,z) are coordinates, e is energy, and d is a derived feature- Euclidean distance between the ...
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How weight vector behave when we initialize the weight to 0 in case of perceptron
While reading in book i encountered this statement
Now, the reason we don't initialize the weights to zero is that the learning rate (eta) only has an effect on the classification outcome if the ...
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Everything is classified as background by segmentation model
I am training a U-NET model for medical image segmentation. Problem is that the binary masks that im using to train the model mostly consist of background pixels and a very small region of the whole ...
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Advice on deep learning PC build using dual 4090s
I’m an engineering grad student, and I’ve been tasked with finding parts for building a shared workstation for my lab. Our work includes deep learning, computer vision, network analysis, reinforcement ...
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How to create modeling data for predciting Customer Lifetime Value? and Definitions of Customer Lifetime Value
I'm trying to build this CLTV model for customers coming to purchase products over time but I'm new to CLTV, so got some questions to clarify:
Since each customer was acquired in different time point,...