Questions tagged [models]

For questions related to modelling external environment, functional models tuned through convergent methods such as artificial networks or fuzzy logic containers, loss models, semantic models, model-based reasoning, or other kinds of models used in AI research, development, or practice.

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17 views

Which AI model to analyse and organize a random document?

I'm new to ML and AI. I am working on a machine learning project where I create a model that is able to analyze and organize a random document. Now I've been doing a lot of research in this field, but ...
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17 views

Correct way to stop Python CLI tensorflow model (model_main_tf2.py) training? [closed]

I've read through several into webpages and as many documents as I can but as far as I can tell were supposed to Ctl-C to terminate training? Is that correct? If I kill the process using ...
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20 views

searching for finding some mental disorder simulation by AI models

I have tried to find some AI models which could create one sense of the autism simulated video on the below questions: Searching for finding the similarity of the Autism verbal brain functionality ...
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About trying simulating the Autism brain activities by AI Models

I am trying to simulate the below Autism simulation's video by AI models, the scenario could be seen in the below sense of the video: In my hypothesis the visual part of the brain is bombarded by the ...
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16 views

Which model should I use?

I want to create something like a recommendation system based on tensorflow/keras. Initially the system will have some arbitrary (random or user-chosen) inputs and generate some image based on those ...
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14 views

About the proper method to make some mathematical model from AI trained Weights (Parameters)

If possible, I like to know about the available methods for creating the summarized mathematical models from the trained AI weights. For example, I need to make some summarized model from the trained ...
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1answer
37 views

Are there any animation tools available to visualise and simulate deep neural networks? [closed]

Deep learning researchers have to work with a lot of models. The models may include different types of Layers: They include convolutional neural network layers, recurrent neural network layers, batch ...
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1answer
72 views

Why is the validation accuracy lower in case of CNN?

I fed the same set of 1.4 million data to two different models: MLP CNN model In both cases, I used the same parameters and hyperparameters. The CNN is showing comparatively lower accuracy (80%) ...
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19 views

How to ensemble two different computer vision models?

I have prepared two distinct models: Representing contour of the image Representing edges of the image. I would like to create a model which can take advantage of both models in predicting data. May ...
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1answer
31 views

My weights for binary classification are not getting updated [closed]

I am very new to this pytorch and neural networks.I am stuck in training one model since last 1 week. My model paramters are not getting updated after each epoch. Also,...
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29 views

Non-locally Electrically Programmable Logic Gates - Technological Advances Progress

Preface: I’d like to clarify that I understand what a relay is and that a PLC uses a fairly conventional microprocessor that only digitally establishes logical logic gate configuration as a digitally ...
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28 views

How to generate text descriptions from keywords?

I wonder how can I build a neural network which will generate text description from given tag/tags. Let's assume I have created such data structure: ...
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52 views

What is a model lineage?

We know about the lineage of datasets. Is there anything called "(ML) model lineage". What are all the works that had been remarkable regarding "model lineage"? There are few links ...
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34 views

Which approach best suits vector encodings?

I want to build a model that when given two vectors, outputs the probability of one vector being the encoded form of the other. I have 2 strategies for this: (Dataset available) I can directly feed ...
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42 views

Difference between a distribution model and a sampling environment in Reinforcement Learning

The book from Sutton and Barto define a model in Reinforcement Learning as "something that mimics the behavior of the environment, or more generally, that allows inferences to be made about how ...
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1answer
1k views

Is there a machine learning model that can be trained with labels that only say how "right" or "wrong" it was?

I'm trying to find the name for a model that is used to output a decision (maybe something like right, left, or ...
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3answers
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What are the differences between an agent and a model?

In the context of Artificial Intelligence, sometimes people use the word "agent" and sometimes use the word "model" to refer to the output of the whole "AI-process". For ...
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4answers
475 views

How to embed/deploy an arbitrary machine learning model on microcontrollers?

Say I have a machine learning model trained on a laptop and I then want to embed/deploy the model on a microcontroller. How can I do this? I know that TensorflowLite Micro generates a C header to be ...
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39 views

How and why do state-of-the-art models in medical segmentation differ from general segmentation models?

I am just getting into medical image segmentation and have been able to understand the state-of-the-art architectures, like Double UNet, UNet++, and Multiresunet. What I haven't understood yet: Why ...
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4answers
601 views

What is the fundamental difference between an ML model and a function?

A model can be roughly defined as any design that is able to solve an ML task. Examples of models are the neural network, decision tree, Markov network, etc. A function can be defined as a set of ...
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1answer
54 views

Aside from specific training sets, what distinguishes the capabilities of different AI implementations?

(Disclaimer: I don't know much about ML/AI, besides some basic ideas behind it all.) It seems like ML/AI models can often be boiled down to statistics, where certain levers (weights) get fine-tuned ...
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1answer
631 views

The truth value of an array with more than one element is ambiguous - Loading a model saved in h5 format keras 2.2.4 [closed]

I'm having a problem when loading a model in keras: model = load_model('model.h5', custom_objects={'mean_iou': metrics.mean_iou}) As an error I get: ...
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1answer
38 views

Is there a complement to GPT/2/3 that can be trained using supervised learning methods?

This is a bit of a soft question, not sure if it's on topic, please let me know how I can improve it if it doesn't meet the criteria for the site. GPT models are unsupervised in nature and are (from ...
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1answer
77 views

What is the difference between parametric and non-parametric models?

A model can be classified as parametric or non-parametric. How are models classified as parametric and non-parametric models? What is the difference between the two approaches?
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19 views

Literature on computational modelling involving neuronal ensemblies

Straying from the current trends in deep learning, there is an, arguably, interesting idea of neuronal ensembles possibly providing an alternative to the current "layered feature detectors" ...
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1answer
73 views

What are some examples of functions that machine learning models compute?

My simple understanding of AI is that it is based on a mathematical model of a problem. If I understood correctly, the model is a polynomial equation and its weights are calculated by training the ...
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1answer
22 views

How to combine specific CNN models that work better at slightly different tasks?

I'm not sure how to describe this in the most accurate way but I'll give it a shot. I've developed a Inception-Resnet V2 model for detecting audio signals via spectrogram. It does a pretty good job ...
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2answers
75 views

How can I be sure that the final model, trained on all data, is correct?

The 'by the book' method of delivering final machine learning models is to include all data in the final training (including validation and test sets). To check robustness of my model I use randomly ...
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76 views

Is it good practice to save NLP Transformer based pre-trained models into file system in production environment

I have developed a multi label classifier using BERT. I'm leveraging Hugging Face Pytorch implementation for transformers. I have saved the pretrained model into the file directory in dev environment. ...
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1answer
34 views

Detect data in tables of roughly the same structure

I would like to train a model that serializes a table of nutrition facts into it's values. The tables can vary in form and colour, but always contain the same set of keys (e.g. carbs, fats). Examples ...
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1answer
85 views

What are the main differences between a language model and a machine translation model?

What are the main differences between a language model and a machine translation model?
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1answer
80 views

Why is the hypothesis function $h_{\theta}(x)$ equivalent to $E[y | x; \theta]$ in generalised linear models?

Reading through the CS229 lecture notes on generalised linear models, I came across the idea that a linear regression problem can be modelled as a Gaussian distribution, which is a form of the ...
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22 views

Training a model for text document transformation?

I have a bunch of text documents, split into source documents and transformed documents. These text documents have multiple lines and are edited at specific locations, in a specific way. I make use ...
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2answers
53 views

Is it theoretically possible (or impossible) that principal component analysis worsens the performance of the model?

In case I had a prediction model and decided to add a PCA step prior to the model, is it theoretically possible/impossible that the number of output dimensions that is better for all tests may perform ...
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0answers
35 views

Is there a theory that captures the following ideas?

A big class of problems that are relevant in today's society are full of uncertainty and are also sometimes computationally intractable. Along our lives we come to realize that we are solving the same ...
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1answer
33 views

How to work on different models for a given problem?

I am working on the MNIST data on my own. The idea is to use different values for the number of hidden layers, number of nodes in a given layer, etc. How do you organize these things while you are ...
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1answer
94 views

What is the difference between FC and MLP in as used in PointNet?

I am trying to understand the PointNet network for dealing with point clouds and struggling with understanding the difference between FC and MLP: "FC is fully connected layer operating on each ...
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1answer
52 views

Neural networks with internal dynamics in the state-space form

Neural networks with feedback (Hopfield, Hamming, etc.) differ from ordinary neural networks (multilayer perceptrons, etc.), which turns them into a dynamic element with its own internal dynamics (if ...
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3answers
117 views

Isn't a simulation a great model for model-based reinforcement learning?

Most reinforcement learning agents are trained in simulated environments. The goal is to maximize performance in (often) the same environment, preferably with a minimum amount of interactions. Having ...
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1answer
92 views

What is the difference between model and data distributions?

Is there any difference between the model distribution and data distribution, or are they the same?
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1answer
262 views

What are pros and cons of Bi-LSTM as compared to LSTM?

What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
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2answers
5k views

What are the main differences between skip-gram and continuous bag of words?

The skip-gram and continuous bag of words (CBOW) are two different types of word2vec model. What are the main differences between them? What are the pros and cons of both methods?
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87 views

What are the advantages and disadvantages of extrinsic and perplexity model evaluation in NLP?

In the video Evaluation and Perplexity by Dan Jurafsky, the author talks about extrinsic and perplexity evaluation in the context of natural language processing (NLP). What are the advantages and ...
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1answer
57 views

What is the current state-of-the-art in unsupervised cross-lingual representation learning?

What is the current state-of-the-art in unsupervised cross-lingual representation learning?
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221 views

How get matrix of word embeddings in FastText of gensim?

I try get the matrix embedding of my model but I can't because although this code gives no error it never ends running. The code is: ...
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36 views

Using ML for Enemy Generation in Video Games

I am attempting to make a 2-D platformer game where the player traverses through an evil factory that is producing killer robots. The robots spawn at multiple specific locations in each level and ...
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1answer
121 views

YOLOv3 Model Structure: Why is filters = (classes + coords + 1) * num?

Here's a tutorial about doing custom training of YOLO (Darknet): https://medium.com/@manivannan_data/how-to-train-yolov3-to-detect-custom-objects-ccbcafeb13d2 The tutorial guides how to set values in ...
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29 views

What models will you suggest to use in Industrial Anomaly Detection and Predictive analysis on live streamed data?

I have been working on industrial data, that is fed live, I want to explore a few models which might suit for this the best. The data are KPI data from the manufacturing Industry.
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2answers
237 views

Will AI always depend on models and thus approximations?

In section 3 of the paper The Limits of Correctness (1985) Brian Cantwell Smith writes When you design and build a computer system, you first formulate a model of the problem you want it to solve, ...
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581 views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...