Questions tagged [machine-learning]
Machine learning algorithms build a model of the training data. The term "machine learning" is vaguely defined; it includes what is also called statistical learning, reinforcement learning, unsupervised learning, etc. ALWAYS ADD A MORE SPECIFIC TAG.
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Output from Model A as Training Data into Model B
Not sure this is the right place to ask this question, but I'm having a disagreement with a colleague on this idea.
Let's say we have a dataset comprised of "unclean" strings. The end goal ...
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Model suggestion to predict a ratio
I have a project where I have a data on companies (one variable being their number of clients and if they have a had a compliance issue.) Im trying to build a model to find a ratio of employees to ...
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How to Estimate GPU Memory for training and inference, Data Requirements, and Training Time for Large Language Models?
Today, I faced this question during an interview for an ML Engineer position. I didn't answer it perfectly at the time. How should I answer it ideally?
Assume we have models like Transformer, BERT, ...
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There are statistical models for nonindependent/multilevel data (e.g., Mixed Models). Is there an approach for multilevel data in Machine Learning?
There are many cases of multilevel/nested/hierarchical data: people in schools, schools in counties, trials within a person, web sessions or mobile sessions within a person, etc.
In traditional ...
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Bounds on Rademacher complexity of intinite class of bounded functions
Suppose I have a class $\mathcal{F}$ of bounded functions $f : \mathcal{X} \to \mathcal{Y}$ , i.e. there exists $M < \infty$ such that for all $ x \in \mathcal{X}$, for some norm $ \lVert \cdot \...
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Determining origin column for values in DataFrame [closed]
I have a DataFrame with n columns represented as [col1, col2, col3, ..., coln] and a set of values {x1, x2, ..., xn}. My goal is to identify from which column xi is most likely to originate, given ...
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Efficient pooling to extract global embedding from local features (for LiDAR point clouds)
Problem:
I have 3d point cloud data (autonomous driving setting) and a point cloud encoder (MinkUNet) that extracts local features from them. What are suitable pooling techniques to map those local (...
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If there are cubic polynomial features, then isn't this a polynomial regression, not a linear regression? [duplicate]
I have the following problem:
Consider a Linear Regression problem with two features. Based on your visualisation of these 2D features, $x_1$ and $x_2$, on the training set, you noticed that using ...
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Meta-learner trained on matched data
I am trying to estimate the average treatment on the treated.
I have used propensity score matching first, to create the control and treatment groups.
I end up having quite small group sizes (1500 ...
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Weight initialisation for neural networks - should they be different for each observations or the same?
I am implementing myself a Neural Network with feedforward and backpropagation with gradient descent to understand better how things work.
After setting up the entire algorithm, I still have a huge ...
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ADALINE simple implementation with 2 features bug
I am reading Machine Learning with PyTorch and Ski-kit learn book by Sebastian Raschka
While plotting the decision boundary (a line in this case, since the number of features considered = 2) I can't ...
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Predictive Maintenance of factory parts
I'm training a model to perform predictive maintenance of a particular part in a factory. I have performed data cleaning like removing the null, duplicate values, removing the highly correlated ...
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The meaning of linear transformation in a batch norm revisited
I'm reading BatchNorm Wikipedia page, where they explain that BatchNorm.
I think the actual formulas are easier than words in this case. The norm statistics are calculated as:
$$\large{\displaystyle \...
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How can different models based on different sets of predictors be combined to significantly improve the model performance?
I have two machine learning models for predicting some continuous variable $y$, say $y=f_1(X_1, \theta_1)$ and $y=f_2(X_2, \theta_2)$, and these models are of the same type (ANN). $X_1$ and $X_2$ ...
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Create 2D representative visualisation clusters from 786D clusters
I have about 60'000 vector embedding of size 786. They divide up neatly into about 10 clusters. I have used K-Means to find the clusters. Now I would like to visualize them. The vectors should be ...
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