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.

425 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
1
vote
0answers
28 views

Difference in trained models between GCP's Google Vision and Firebase's ML kit?

Anyone here know if the image-recognition/text-recognition/etc features of Google Vision API use the same trained models as the image-recognition/text-recognition/etc of Firebase's ML kit? If they don'...
1
vote
0answers
39 views

What methods are there to detect discrimination in trained models?

I've been researching AI regulation and compliance (see my related question on law.stackexchange), and one of the big take-aways that I had is that the regulations that apply to a human will apply to ...
1
vote
0answers
27 views

In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?

I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of ...
1
vote
0answers
47 views

small multinomial Naive Bayes text classification probabilities

When applying multinomial Naive Bayes text classification I get very small probabilities(around 10e-48) so there's no way for me to know which classes are valid ...
1
vote
0answers
70 views

How do GAN's generator actually work?

I have implemented DCGAN's myself and have been studying GAN's for over a month now. Now I am implementing the pggans but I encountered a sentence When we measure the distance between the ...
1
vote
0answers
60 views

Why do we have to solve MDP in each iteration of Maximum Entropy Inverse Reinforcement Learning?

Gradient in Maximum Entropy IRL requires to find the probability of expert trajectories given the reward function weights. This is done in the paper by calculating state visitation probabilities but I ...
1
vote
0answers
47 views

Data to Google Machine Learning

I have a database with hundreds of questions and answers. Would you like to know how I can work on this data in Google Cloud? I have a social network where I have these questions and answers, and I ...
1
vote
0answers
73 views

How to implement AI/ML to classify various types of files

I am working on a task that requires me to classify a large amount of mixed files on a backup drive (more than 10 TB with more than 32 million files) based on content. The included file types are ...
1
vote
0answers
226 views

How To Improve This Sentiment Analysis Model

A.I Community, this is my first post on here I am currently reading, learning and designing models. At the moment I'm working on this sentiment analysis tool; from what I gather sentiment analysis can ...
1
vote
0answers
30 views

Atrous (Dilated) Convolution: How one can compute responses of arbitrarily high dimensions in DCNN?

According to this paper (page 4, bottom-right), atrous convolutions can be used to compute responses of arbitrarily large dimensions in Deep Convolutional Neural Networks. I do not understand how ...
1
vote
1answer
157 views

Capsule Networks - Facial Expression Recognition

I want to experiment Capsule Networks on FER. For now I am using fer2013 Kaggle dataset. One thing that I didn't understand in Capsule Net was in the first conv layer, size was reduced to 20x20 - ...
1
vote
0answers
43 views

Data Interpretation technique

In the model generation, in machine learning (consider supervised) If some data change the previous model function drastically then we should study that data. Does it happen? How to handle such ...
1
vote
0answers
60 views

Will commercialisation and widespread use of A.I in security and surveillance and other household products threaten free will or endanger privacy?

Everything from facial recognition to the google home is coming equiped with A.I and it is being widely used , If autonomously connected to the internet , will A.I pose a threat to privacy or will it ...
1
vote
0answers
33 views

How to factor time into decision trees?

Are decision trees able to be used with time-related data? I've read that decision trees are based on matrices and that ARRAYS of input matrices can be used to factor in time however I can't find an ...
1
vote
0answers
63 views

Simple website and attaching Data Analysis to user information for feedback

I am looking to learn Ai/Machine learning during my spare and need advice on tools used / What to read / How one can integrate machine learning with a simple website for user feedback Scenario: .Net ...
1
vote
0answers
21 views

Social network filtering for specific topic

I created and operate a social network for meeting new people. As a result of the recent FOSTA legislation, it’s imperative that I implement an automated system to prevent users from posting ...
1
vote
0answers
60 views

Learning from events. Supervised, Unsupervised or MDP?

I have a large set of simulation logs for a market simulation of which I want to learn from. The market includes: customers products (subscriptions) The customers choose products and then stick with ...
1
vote
0answers
24 views

Commercial API Q: is there an api for converting vision tags into a caption?

There are many machine learning api for scanning images but they just return a bunch of tags. https://azure.microsoft.com/en-gb/services/cognitive-services/computer-vision/ ...
1
vote
0answers
86 views

Learning algorithm that filters keyboard clicking in audio feeds

When recording audio for screencasts or similar, very often the keyboard is clearly visible and can start to annoy listeners after a while. NN are quiet good at recognizing patterns. Image ...
1
vote
0answers
41 views

How to calculate Adaptive gradient?

In the FaceNet paper there mentions an gradient algorithm called 'AdaGrad'(Adaptive Gradient) referenced to this paper which has apparently been used to calculate the gradient of the Triplet Loss ...
1
vote
0answers
258 views

Analogies and similarity

The more I think about machine learning the more I realize the importance of finding similarities by using analogies as a way of learning. If I want to categorize words into hierarchical tree this ...
1
vote
0answers
60 views

Prove that there might be an Agent function which cannot be implemented by any Agent program

So i really don't get this question because i always thought the agent program is the same as agent's function, but i read somewhere that this is statement might be true so is this statement actually ...
1
vote
0answers
265 views

Application of Ai to task scheduling problems on heterogenous platforms

Let's say we have a cluster of 20-2000 heterogenous compute nodes. Consider for example the parallel solution of the helmholtz equation: Now we want to distribute the solution process and, to make ...
1
vote
0answers
20 views

Can number of Leads be predicted based on previous months

I have a sample set of data about Leads that gets generated every day. Leads are nothing but a user expressing request to be our partner or not. Sample data set is as shown below ...
1
vote
0answers
256 views

Tensorflow: Can't overfit training data with batch size > 1

I coded a small RNN network with Tensorflow to return the total energy consumption given some parameters. There seem to be a problem in my code. It can't overfit the training data when I use a batch ...
1
vote
0answers
72 views

Algorithms that connect neurons to previous layers as well as next

Are there any algorithms, or any evidence to decide or to suggest it would be better to connect a neuron node in a layer l, in a neural network to particular nodes ...
1
vote
0answers
153 views

Natural language processing with a continuous dependent variable

I have a large number of observations. Each observation contains: dependent variable: a scores ranging from 0 - 100 independent variable: a large article I want to know which words or phrases ...
1
vote
0answers
53 views

Decision tree doesn't quite work, is there a better alternative?

I have a problem that I have been trying to use decision trees to solve. There is a data set of pricing information for products sold by a company. The goal is to infer the pricing algorithm for each ...
1
vote
0answers
59 views

Orientation of data set before training simple ANN's

Well, I am new to implementing ANN's and there is something that i want to know. It maybe a bit silly though. I just wanted to know that if we have a simple data set say dependent only on a single ...
1
vote
0answers
157 views

Help with implementing Q-learning for a feedfoward network playing a video game

I want to train a feedforward neural network to play a video game called Puyo Puyo 2, using reinforcement learning. More specifically, I'm trying Q-learning but I'm open to better alternatives. In ...
1
vote
0answers
50 views

Build Android News Recommendation app

Please I am interested in building a news recommendation app that will be powered by artificial intelligence. I have being making a whole lot of research on this and will be glad if somebody can tell ...
1
vote
0answers
185 views

Converting pictures into numerical values

I am working to make my first trained model for image recognition, using the programming language R. First I am attempting to make a function that takes a PNG-image as input, resizes it to 128x128 ...
1
vote
0answers
141 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 ...
1
vote
0answers
86 views

Agent exploration which leads to a negative state where actions are limited

I'm working on a project where I train a Q-learning agent to learn an optimal control policy for a water heater. I've set up a simulation which allows the agent to explore for one year. I then examine ...
1
vote
0answers
95 views

Infer dependent variables to produce output aligned to trained data

Hypothetical example, say I wanted: P(gender,ethnicity|age,hair); so that the input would aligned to a trained dataset of: ...
1
vote
1answer
495 views

How to find partial derivative of softmax w.r.t logits in python

i have trouble implementing back propogation for multi class classification of CIFAR10 dataset My neural network has 2 layers forward propagation X -> L1 -> L2 weights W are initialized as random ...
0
votes
0answers
4 views

How can I develop a reinforcement learning agent that plays memory cards game?

I am new to RL, and I am thinking of doing a little project. The goal of the project is to learn an agent play the memory game with cards. I already created the program for detecting the cards on the ...
0
votes
0answers
8 views

What are the pros and cons of deep learning and machine learning to develop a trading system?

As I want to start coding a new Trading AI in this year (first based on Python and later maybe in C++) I stumbled over the following question: Today, I would like to make a pro/contra list with you ...
0
votes
0answers
7 views

How to output a filter of equal size to the original image in Fully Convolutional Neural networks

I'm trying to perform a segmentation task on images of multiple sizes using fully convolutional neural networks. Currently, I'm using efficientnet as a feature extractor, and adding a deconvolution/...
0
votes
1answer
71 views

Is my GRU model under-fitting given this plot of the training and validation loss?

I was running my gated recurrent unit (GRU) model. I wanted to get an opinion if my loss and validation loss graph is good or not, since I'm new to this and don't really know if that is considered ...
0
votes
1answer
12 views

Pros and Cons of Seq2Seq vs Bidirectional RNN

It seems to me that Seq2Seq models and Bidirectional RNNs try to do the same thing. Is that true? Also, when would you recommend one setup over another? Thanks!
0
votes
1answer
27 views

How does the regression layer in the localization network of a spatial transformer work?

I am trying to understand the spatial transformer network mentioned in this paper https://papers.nips.cc/paper/5854-spatial-transformer-networks.pdf. I am clear about the last two stages of the ...
0
votes
0answers
11 views

Feed data into Keras LSTM layer

I'm trying to understand how to feed data into LSTM layer of Keras, but I'm in trouble and I don't understand how to do it. I've ...
0
votes
0answers
13 views

Computing latent representation for multi-domain regression/classification

Suppose I have a dataset with (X, Y) training samples where X is a 1 dimension, and Y is also 1 dimension. Example: if this is a housing price dataset, X would be an area in square feet, and Y would ...
0
votes
0answers
29 views

Semi-supervised: Can I predict the label of purposely unlabelled observations?

Let's say I have a data set with of length N. A small proportion N2 is labeled. Can I remove some labels and then 'reverse' this action with a trained neural network? I could then use the same process ...
0
votes
0answers
19 views

Steps to train and re-train a good model

I'm still a bit new to deep learning. What I'm still struggling, is what is the best practice in re-training a good model over time? I've trained a deep model for my binary classification problem (...
0
votes
0answers
10 views

What will be the sequence of steps in a human activity recognition model using LSTM?

In the context of these steps detection, tracking, action classification and activity recognition. Which step will be first and further sequence?
0
votes
0answers
16 views

Pytorch deep learning models and tabular data representation

I have quite a naive question regarding Pytorch deep learning models and tabular data representation. So, assume I have a dictionary of tables. Each table has some number of columns: categorical and ...
0
votes
0answers
8 views

Architecture of the encoder in a Bi-GAN?

I know this is a subjective question, but I was thinking how does one decide on their encoder architecture in the case of Bi-directional GANs. The first idea coming to my mind is basically mirroring ...
0
votes
0answers
15 views

Post-classification after inference

I designed a fire detection using Deep Learning based classification approach. In my training dataset, I have both fire and fire smokes are supposed to be detected (all under "fire"; mostly real fires ...

1
5 6
7
8 9