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Welcome to the staging ground for new communities! Each proposal has a description in the "Descriptions" category and a body of questions and answers in "Incubator Q&A". You can ask questions (and get answers, we hope!) right away, and start new proposals.

Activity for mr Tsjolder‭

Type On... Excerpt Status Date
Edit Post #290190 Initial revision 6 months ago
Answer A: What is the technical term for converting a sound recording to a phoneme vector?
I am no specialist on audio processing, but I believe the general task of converting raw audio to discrete symbols is called transcription. However, this does not distinguish whether these symbols are phones, phonemes or text. I strongly suspect that there is no more specific terminology (as in N...
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6 months ago
Edit Post #290026 Initial revision 7 months ago
Answer A: Is LLM fine tuning the same as transfer learning?
TL;DR: Fine-tuning is not the same as transfer learning, but is often a part of transfer learning. The goal of transfer learning is to "transfer" information from one model to some other model. Typically, the goal is to reuse parts of a good-performing, existing model to create a new model (possi...
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7 months ago
Comment Post #290004 Does incremental training refer to [incremental learning](https://en.wikipedia.org/wiki/Incremental_learning)? Also, could you shortly explain why you think they would be the same?
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7 months ago
Edit Post #289179 Post edited:
add section on minimum effort requirement
7 months ago
Comment Post #289983 I would argue that the linked question focuses on what paradigm to use in what context. Furthermore, the question (vaguely) acknowledges the existence of other "learning" terms, but you are definitely right that the list of approaches is a nice addition and I updated the question accordingly.
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7 months ago
Edit Post #289949 Post edited:
add link to wikipedia list of approaches and add tag
7 months ago
Edit Post #290014 Initial revision 7 months ago
Answer A: What is unsupervised learning?
Unsupervised learning covers a variety of different tasks. Depending on the task at hand, different techniques can be used. However, there are a few common paradigms that are used to extract information from unlabelled data. A simple, yet effective method is to create labels from the input data....
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7 months ago
Comment Post #289983 I would argue that the second sentence on the linked page gives a clear answer to the question. If you think it is too technical, then it would be good to include this information in your question. The problem is that my answer would end up being very similar to the information in this second sentenc...
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7 months ago
Comment Post #289981 I think this is a nice write-up. For me, it misses the point a bit on unsupervised learning and I would not use transfer learning to talk about incremental training (which I know best as continual learning). As a matter of fact, I would argue that fine-tuning, which is not specific to LLMs) is more c...
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7 months ago
Comment Post #289983 The page on hyper-parameters on [wikipedia](https://en.wikipedia.org/wiki/Hyperparameter_(machine_learning)) seems to answer this question pretty well. Do you find something confusing about the explanation there?
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7 months ago
Edit Post #289949 Initial revision 7 months ago
Question What types of learning should I know about?
In machine learning there seem to be various types of learning. I commonly hear about - supervised learning, - unsupervised learning, and - reinforcement learning. However, it is not always clear to me how they differ or what paradigm is best used for a particular task. I can also imagin...
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7 months ago
Edit Post #289713 Initial revision 8 months ago
Answer A: Why can't we use linear regression on logits for solving logistic regression problems?
There is the obvious answer that points out that since $y \in \{0, 1\}$, we would end up with invalid values for computing the logits. However, by transforming the labels to have values $\tilde{y} \in \{\varepsilon, 1 - \varepsilon\}$ for some $\varepsilon \in (0, 0.5)$ (also known as label smoothin...
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8 months ago
Edit Post #289179 Post edited:
include prompt engineering, exclude "classical" AI
9 months ago
Comment Post #289268 I have had pretty good experiences with the markdown parsing from [mattermost](https://github.com/mattermost/mattermost). There might be edge cases, but they seem to be able to distinguish between dollar signs used for mathjax and as currency symbol.
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9 months ago
Comment Post #289196 There is definitely room for reconsidering the prompt engineering aspect for ML. However, the idea for the ML community would be to gather people who are interested in the technical aspects of ML, rather than people who just want to participate in the hype without caring for the technical side. Ther...
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9 months ago
Edit Post #289266 Initial revision 10 months ago
Question Why can't we use linear regression on logits for solving logistic regression problems?
Consider a machine learning problem with inputs $\boldsymbol{X} \in \mathbb{R}^{N \times D}$ and corresponding labels $\boldsymbol{y} \in \mathcal{Y}^N$. When the problem is to solve a regression task, $\mathcal{Y}^N = \mathbb{R}^N$ and we can use linear regression model, $$\hat{\boldsymbol{y}} =...
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10 months ago
Edit Post #289198 Initial revision 10 months ago
Question Would it be possible to enable special features in the Incubator Q&A?
Is it possible to have special features enabled in the Incubator Q&A? I have tried to port one of my an answers for a question on Machine Learning, but it was written for markdown with MathJax support. Without the MathJax support, the post is practically unreadable. Would it be possible to enabl...
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10 months ago
Edit Post #289197 Initial revision 10 months ago
Answer A: What are the support vectors in a soft-margin SVM
The goal of a soft-margin or C-SVM is to solve the following minimisation problem: $$\min{\boldsymbol{w}, b} \frac{1}{2} \|\boldsymbol{w}\|^2 + C \sumi \xii$$ subject to $$\forall i : \begin{aligned}yi (\boldsymbol{w} \cdot \boldsymbol{x}i + b) - 1 + \xii &\geq 0 \\ \xii &\geq 0\end{aligned},$$ ...
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10 months ago
Comment Post #289179 therefore it might make sense to set up a second section. Maybe it could be an explicit separation between technical and non-technical questions. However, I am not sure if it is a good idea to have both areas in the same community. Alternatively, we could make prompt-engineering on-topic, but it woul...
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10 months ago
Edit Post #289185 Initial revision 10 months ago
Question What are the support vectors in a soft-margin SVM
I know what Support Vector Machines (SVMs) are and how they work, but I regularly get confused by what exactly the support vectors are. In case of linearly separable data, the support vectors are those data points that lie (exactly) on the borders of the margins. After all, these are the only p...
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10 months ago
Edit Post #289179 Initial revision 10 months ago
Answer Machine Learning
The Machine Learning (ML) community aims to provide a platform for anyone interested in helping computers learn from data. We mainly target people with backgrounds in data science, machine learning and data visualisation, but also statisticians, computer scientists and anyone looking to learn about ...
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10 months ago
Comment Post #289124 As an ML researcher this feels like the proposal for a Q&A about ML tools (similar to how programming languages are the tools of programmers): - latest models ~ latest programming language - suitability of tasks ~ what language for what task? - API usage ~ language syntax - model deployme...
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10 months ago
Edit Post #289163 Initial revision 10 months ago
Answer A: Free alternatives to GPT-3/4?
Technically, chat-GPT (GPT-3.5) is also freely accessible via https://chat.openai.com Possible alternatives are: - TII's Falcon - LAION's Open Assistant - Mosaic's MPT - Google's Bard - Anthropic's Claude-2 - Meta's LLama 2 - ... This list is probably incomplete, especially if we ...
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10 months ago