Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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1answer
19 views

How to detect any native language when written in english characters?

assume somebody knows only to write in english. If he writes words of any other language(example: hindi, french, latin) using the english alphabet, how can I detect that language(example: hindi, ...
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0answers
19 views

Finding the right model

I am searching for an apt supervised model for the following use case: If i have a sum (say 10) and it can to distributed in a predefined number of bins (say 5) in a number of ways for instance: ...
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1answer
47 views

Eligibility vector for softmax policy with policy gradients

There is this nice result for policy gradients that the gradient of some performance measure, $\nabla v_{\pi_{\theta}}(s_0)$ (here, in the episodic case for the starting state $s_0$ and policy $\pi$, ...
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0answers
13 views

Dataset of phonemes

So this is more of a broad question but I am looking for a dataset of clear audio, a corresponding transcript (optional), and most importantly a list of all the phonemes (https://www.merriam-webster....
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3answers
29k views

How can neural networks deal with varying input sizes?

As far as I can tell, neural networks have a fixed number of neurons in the input layer. If neural networks are used in a context like NLP, sentences or blocks of text of varying sizes are fed to a ...
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1answer
79 views

Why is this ResNet50 misclassifying objects?

I'm new to Deep Learning, and I have some conceptual problems. I followed a simple tutorial here, and trained a model in Keras to do image classification on 10 classes of logos. I prepared 10 classes ...
2
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0answers
31 views

Can learned feature vectors be considered a good encryption?

Considering I have some neural network that, using supervised learning, transforms a string into a learned feature vector where "close" strings will result into more close vectors. I know that since ...
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8answers
27k views

Why is Python such a popular language in the AI field?

First of all, I'm a beginner studying AI and this is not an opinion oriented question or one to compare programming languages. I'm not implying that Python is the best language. But the fact is that ...
2
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0answers
22 views

Correlating two models to predict the output of one that corresponds to an output of the other

I am currently working on a problem and now got stuck to implement one of it's steps. This is a simple attempt to explain what I am currently facing, which is something that I am aiming to implement ...
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1answer
852 views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
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1answer
355 views

What is the relationship between these two taxonomies for machine learning with neural networks?

Could you please let me know which of the following classification of Neural Network's learning algorithm is correct? The first one classifies it into: supervised, unsupervised and reinforcement ...
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2answers
190 views

What is the role of the hidden vectors in restricted Boltzmann machines?

I'm learning about the restricted Boltzmann machine (RBM), and I just came up with two naive understandings of this model. But it seems these two understandings are so different. My first ...
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0answers
25 views

Is logistic regression used for unconstrained or constrained optimisation problems?

Is logistic regression used for unconstrained or constrained optimization problems, and why?
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1answer
23 views

Is it possible to use AI for detecting the volume of a cup

I was just wondering if it's possible to use Machine Learning to train a model from a dataset of images of cups with a given volume in the image and then use object detection to detect other cups and ...
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1answer
29 views

Relationship between training accuracy and validation accuracy

During model training, I noticed various behaviour in between training and validation accuracy. I understand that 'The training set is used to train the model, while the validation set is only used to ...
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0answers
52 views

Which machine learning algorithms can be used to build a recommendation system?

I am working on building a recommendation engine. I need to build a model that recommends similar items. Currently, I am using the Nearest Neighbor algorithm present in ...
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0answers
27 views

Does CNN Model accuracy increase if I fit it twice

As I train my CNN model I realised that fitting model twice, ie. running again this code ...
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1answer
36 views

How are the inputs passed to the neural network during training for the XOR classification task?

Let's suppose we have to train a neural network for the XOR classification task. Are the inputs $(00, 01, 10, 11)$ inserted in a sequential way? For example, we first insert the 00 and change the ...
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1answer
40 views

Analyzing vibration using machine learning

I would like a few suggestions on an idea that I have - I am trying to make a musical instrument (percussion), whilst just having a PVC disc. I am hitting the disc in a variety of styles (in order to ...
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0answers
29 views

What ML algorithms would you suggest in fraud detection?

There are a lot of ML algorithms suggested for fraud detection. Now, I have not been able to find a general overview for all of them. My goal is to create this overview. What algorithms would you ...
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0answers
24 views

Drug Review dataset - approach

I am trying to experiment using the Drug Review open dataset https://archive.ics.uci.edu/ml/datasets/Drug+Review+Dataset+%28Drugs.com%29 I need to answer questions from a domain perspective, such ...
3
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1answer
57 views

How can I minimise the false positives?

I have 50,000 samples. Of these 23,000 belong to the desired class $A$. I can sacrifice the number of instances that are classified as belonging to the desired class $A$. It will be enough for me to ...
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1answer
42 views

Prerequisites for Andrew Ng's Machine Learning Course

I am planning to enroll for Andrew Ng's Machine Learning course https://www.coursera.org/learn/machine-learning. I've no background in math. Is it OK if I start the course and learn math as and when ...
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1answer
132 views

What is the best machine learning algorithm to select best 3 variable combinations?

I have 10 variables as like below V1=1, V2=2, V3=3, V4=4, V5=5, V6=6, V7=7, V8=8, V9=9 and V10=10 Note : Each variable can have any value Now I want to select the best 3 variables combination as ...
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2answers
51 views

Knowledge encapsulation in machine learning

The thing about machine learning (ML) that worries me is that "knowledge" acquired in ML is hidden: we usually can't explain the criteria or methods used by the machine to provide an answer when we ...
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1answer
39 views

What is the difference between Kaldi and DeepSpeech speech recognition systems in their approach?

I would like to know how do Kaldi and DeepSpeech speech recognition systems differ algorithmically? Which one would be more accurate for continuous speech in time?
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1answer
71 views

Price difference predictions curve almost vanished

With a team, we are studying how it is possible to predict the price movement with high-frequency. Instead of predicting the price directly, we have decided to try predicting price difference as well ...
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0answers
16 views

The membership function of Consequents (Outputs) in Fuzzy classifier

The problem in Iris data is to classify three species of iris (setosa, versicolor and virginica) by four-dimensional attribute vectors consisting of sepal length (x1) sepal width (x2) petal length (...
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0answers
27 views

Interpretability of feature weights from Gaussian process classifier

Suppose I trained a Gaussian process classifier with a linear kernel (using GPML toolbox) and got some feature weights for each input feature. My question is then: Does it/When does it make sense ...
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0answers
10 views

Why would the application of kernelization prevent underfitting

"Why would the application of kernelization prevent underfitting" I read in some paper that applying kernelization would prevent you from underfitting. Why is that? Source: http://www.cs.cornell.edu/...
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0answers
44 views

Why would the application of boosting prevent underfitting

"Why would the application of boosting prevent underfitting" I read in some paper that applying boosting would prevent you from underfitting. Why is that? Source: http://www.cs.cornell.edu/courses/...
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10answers
13k views

How can an AI train itself if no one is telling it if its answer is correct or wrong?

I am a programmer but not in the field of AI. A question constantly confuses me is that how can an AI be trained if we human beings are not telling it its calculation is correct? For example, news ...
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0answers
11 views

Which algorithm and architecture to use for 1:1 matrix transformation of an 8X8 dimension?

I would like to map the simplest 8X8 matrices, one to one, but am not sure which AI algorithm would give the best performance. I am thinking about the DeepLearning4j, however, I don't know which ...
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1answer
64 views

Will BERT embedding be always same for a given document when used as a feature extractor

When we use BERT embeddings for a classification task, would we get different embeddings every time we pass the same text through the BERT architecture? If yes, is it the right way to use the ...
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3answers
2k views

How can AI techniques be used in software testing?

How can Artificial Intelligence be applied to software testing?
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3answers
83 views

How do you interpret this learning curve?

Loss is MSE; orange is validation loss, blue training loss. The task is NN regression (18 inputs, 2 outputs), one layer 300 hidden units. Tuning the lr, mom, l2 regularization parameters this is the ...
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2answers
46 views

Oposite type of predictions for unbalanced dataset

I have a big dataset (28354359 rows) that has some blood values as features (11 features) and the label or outcome variable that tells whether a patient has a virus caused by a Neoplasm or not. The ...
2
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2answers
93 views

What is probability distribution in machine learning?

If we were learning or working in machine learning field then we frequently come across this term probability distribution. I know what probability, conditional probability and probability ...
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1answer
35 views

What would be the steps to create an sentiment analysis chatbot?

We have been assigned a project, in which we have to create a chatbot which will ask question, take the replies, analyse them and give an approximate assessment of the current emotional state of the ...
3
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1answer
24 views

Can non-sequential deep learning models outperform sequential models in time series forecasting?

Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? I know this question is not very specific, but I experienced this when ...
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0answers
29 views

Difference in the code structure of RNN and CNN

I understand that in general RNN is good for time series data and CNN image data, and have noticed many blogs explaining the ...
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0answers
26 views

Is it possible to create an AI/ML model to hack into any system? Or is there one? [closed]

Is it possible to create an AI/ML model to hack into any system? Or is there one? If there is one, how it can be prevented?
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0answers
33 views

Can supervised learning be used to solve the inverted pendulum problem?

I know that reinforcement learning has been used to solve the inverted pendulum problem. Can supervised learning be used to solve the inverted pendulum problem? For example, there could be an ...
2
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1answer
101 views

Anomaly Detection in distributed system using generated log file

I am developing an AI tool for anomaly detection in a distributed system.  The system supports an interface that combines several individual logs into a single log file generating approx. 7000 entries/...
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1answer
129 views

Tuning the parameters of Particle swarm optimization (PSO)

To tune the parameters of Particle swarm optimization (PSO), there are two methods offline and online. In offline manner, the meta-optimization is used to tune the parameters of PSO by using another ...
2
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1answer
64 views

Are there any public real-life code examples of ML applications in Python?

Problems I often face at work usually differ from tutorial or book-like examples so I end up with a code that works but it's not elegant and takes too much time to write. I wanted to ask you if there ...
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0answers
22 views

How to change the architecture of my simple sequential model

I'm new to Deep Learning with Keras. With some tutorials online for cat vs non-cat classification, I was able to compile this simple architecture for my own ...
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0answers
19 views

What are examples of models for traffic sign detection that can be easily implemented?

I'm working on a college project about traffic sign detection and I have to choose a paper to implement it, but I have basic knowledge of TensorFlow and I'm afraid of choosing a paper that I can't ...
0
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1answer
26 views

Can I perform multiclass classification when the number of features is less than the number of targets?

Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I ...
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2answers
64 views

What is the difference between a learning algorithm and a hypothesis?

What's the distinction between a learning algorithm $A$ and a hypothesis $f$? I'm looking for a few concrete examples, if possible. From what I understand, one way to vary the hypothesis $f$ would be ...