Questions tagged [training]

For questions about training networks, rules systems, or other AI system components.

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11
votes
3answers
7k views

How to train a neural network for a round based board game?

I'm wondering how to train a neural network for a round based board game like, tic-tac-toe, chess, risk or any other round based game. Getting the next move by inference seems to be pretty straight ...
9
votes
3answers
598 views

Why initial weights in neural network are randomized?

This might sound silly to someone who has plenty of experience with neural networks but it bothers me... I mean randomizing initial weights might give you better results that would be somewhat closer ...
9
votes
1answer
15k views

Design AI for log file analysis

I'm developing an AI tool to find known equipments' errors and find new patterns of failure. This log file is time based and has known messages (information and error).I'm using a JavaScript library ...
7
votes
5answers
974 views

How can action recognition be achieved?

For example, I would like to train my neural network to recognize the type of actions (e.g. in commercial movies or some real-life videos), so I can "ask" my network in which video or movie (and at ...
7
votes
2answers
188 views

What is the machine learning approach based on human learning?

I once came across a neural network being trained without back-propagation or genetic algorithms (or using any kind of data sets). It was based on how the human brain learns and adjusts its ...
7
votes
1answer
368 views

Why does 'loss' change depending on the number of epochs chosen?

I am using Keras to train different NN. I would like to know why if I increment the epochs in 1, the result until the new epoch is not the same. I am using shuffle=False, and np.random.seed(2017), and ...
7
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0answers
78 views

Will quantum computing have any kind of effect on the development of AI?

Recently, according to some reports Google achieved something called 'Quantum Supremacy'. Whether its true or not remains to be seen. But my question is does Quantum Computers or the principle they ...
7
votes
3answers
246 views

Can some one help me understand this paragraph from Nvidia's progressive gan paper?

Furthermore, we observe that mode collapses traditionally plaguing GANs tend to happen very quickly, over the course of a dozen minibatches. Commonly they start when the discriminator overshoots, ...
6
votes
2answers
153 views

Shortening the development time of a neural network

I am developing an LSTM for sequence tagging. During the development, I do various changes in the system, for example, add new features, change the number of nodes in the hidden layers, etc. After ...
6
votes
2answers
2k views

Why L1/L2 regularization technique did not improve my accuracy?

I am training a Multilayer Neural Nets with 146 samples (97 for training set, 20 for validation set and 29 for testing set). I am using: automatic differentiation, SGD method, fixed learning rate + ...
6
votes
1answer
93 views

Q-Learning the generic maze solution

After doing some exercices on Q-learning for maze solving, I wondered : my q-learning algorithms solve only ONE maze. The AI doesn't learn how to solve mazes, so how can I achieve it ? For instance ...
6
votes
3answers
275 views

AI composing music

Do you know what AI model would be best for let it learn composing music? I really don't know where to start there. Are there some good papers out there? I would say, if I use a NN, my only option ...
6
votes
1answer
123 views

How do I predict if it is rainy or not?

I'm building a weather station, where I'm sensing temperature, humidity, air pressure, brightness, $CO_2$, but I don't have a raindrop sensor. Is it possible to create an AI which can say if it's ...
6
votes
2answers
128 views

Evolving network in game

So I wrote simple feed forward neural network that plays tic-tac-toe: 9 neurons in input layers: 1 - my sign, -1 - opponent's sign, 0 - empty; 9 neurons in hidden layer: value calculated using Relu; ...
5
votes
5answers
2k views

How does an activation function's derivative measure error rate in a neural network?

A blog post called "Text Classification using Neural Networks" states that the derivative of the output of a sigmoid function is used to measure error rates. What is the rationale for this? I ...
5
votes
1answer
1k views

What are the state space and the state transition function in AI?

I'm studying for my AI final exam, and I'm stuck in the state space representation. I understand initial and goal states, but what I don't understand is the state space and state transition function. ...
5
votes
3answers
54 views

What should we do when we have equal observations with different labels?

Suppose we have a labeled data set with columns $A$, $B$, and $C$ and a binary outcome variable $X$. Suppose we have rows as follows: ...
5
votes
1answer
303 views

What happens to the training data after your machine learning model has been trained?

I am completely new to all this, for the life of me I can't find the answer to this question anywhere on Google. What happens after you have used machine learning to train your model? What happens to ...
5
votes
1answer
75 views

Why evolutionary training of neural networks is not popular?

Evolutionary algorithms are mentioned in some sources as possible to be used to train a neural network (finding weights, not hyperparameters), however I have not heard about one practical application ...
5
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2answers
88 views

What defines a good dataset in Deep Learning approach?

Scenario: I am trying to create a dataset with images of choice for different animal classes. I am going to train those images for classification using CNN. Problem: Lets assume I somehow don't have ...
5
votes
1answer
154 views

Is it feasible to train a Machine Learning Model (with image inputs) in an average personal computer?

There are lots of examples of machine learning systems that can recognize objects and extract other information from images with very high precision. To train the models of such systems is necessary (...
5
votes
3answers
1k views

TensorFlow batch learning

I used the example at - https://github.com/aymericdamien/TensorFlow-Examples/blob/master/examples/5_DataManagement/tensorflow_dataset_api.py - to create my own classification model. I used different ...
5
votes
1answer
37 views

Why do very deep non resnet architectures perform worse compared to shallower ones for the same iteration? Shouldn't they just train slower?

My understanding of the vanishing gradient problem in deep networks is that as backprop progresses through the layers the gradients become small, and thus training progresses slower. I'm having a hard ...
4
votes
2answers
839 views

What is the “thing” which is trained in AI model training

I am a newbie in the fantastic AI world, I have started my learning recently. After a while, my understanding is, we need to feed in tremendous data to train a or many models. Once the training is ...
4
votes
2answers
319 views

Iteratively and adaptively increasing the network size during training

For an experiment that I'm working on, I want to train a deep network in a special way. I want to initialize and train a small network first, then, in a specific way, I want to increase network depth ...
4
votes
2answers
160 views

Use Machine Learning/Artificial Intelligence to predict next number (n+1) in a given sequence of random increasing integers

The AI must predict the next number in a given sequence of incremental integers (with no obvious pattern) using Python but so far I don't get the intended result! I tried changing the learning rate ...
4
votes
1answer
129 views

What approach should I use to detect faces in video game footage?

I have set myself the challenge of detecting the locations of players/bots in videos of a well known first person shooter game (this is for a youtube series I'm planning on doing). I'm not sure which ...
4
votes
2answers
151 views

As a starter: what is the form of training data for image processing

What we are doing in the image processing training. We are storing some form of data which is going to act as the knowledge or experience of the system. In which form can the system store it's ...
4
votes
1answer
61 views

What are state-of-the-art ways of using greedy heuristics to initially set the weights of a Deep Q-Network in Reinforcement Learning?

I am interested in the current state-of-the-art ways to use quick, greedy heuristics in order to speed up the learning in a Deep Q-Network in Reinforcement Learning. In classical RL, I initially set ...
4
votes
1answer
175 views

What can be done to correct for sampling bias introduced from (noisy) training data while training a DNN?

The obvious solution is to ensure that the training data is balanced - but in my particular case that is impossible. What corrections can one perform in such a scenario? I know that my training data ...
4
votes
1answer
44 views

How to compare the training performance of a model on different data input?

So I have a deep learning model and three data sets (images). My theory is that one of these data sets should function better when it comes to training a deep learning model (meaning that the model ...
4
votes
2answers
71 views

How long has it taken for autonomous driving cars to be being sold and used on the roads today?

I remember the first time hearing about google trying to make driverless cars. That was YEARS ago! These days, I'm beginning to learn about Neural Nets and other types of ML and I was wondering: ...
4
votes
1answer
340 views

How would you encode your input vector/matrix from a sequence of moves in game like tasks to train an AI? e.g. Chess AI?

I've seen data sets for classification / regressions tasks in domains such as credit default detection, object identification in an image, stock price prediction etc. All of these data sets could ...
3
votes
3answers
409 views

Why should weights of Neural Networks be initialized to random numbers?

Premise Ok, I know that this question was asked before on ai.SE, on stats.SE and also on SO. So I did my homework in checking before posting my question, but none of them has an answer that fully ...
3
votes
2answers
63 views

Is there a way to define the boundaries of the optimal size of a training set?

At a related question in Computer Science SE, a user told: Neural networks typically require a large training set. Is there a way to define the boundaries of the "optimal" size of a training set ...
3
votes
4answers
186 views

What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
3
votes
2answers
117 views

How do biological neurons weights get initialized?

When trying to map artificial neuronal models to biological facts it was not possible to find an answer regarding the biological justification of randomly initializing the weights. Perhaps this is ...
3
votes
3answers
370 views

What is the name of an AI system that learns by trial and error?

Imagine a system that controls dampers in a complex vent system that has an objective to perfectly equalize the output from each vent. The system has sensors for damper position, flow at various ...
3
votes
1answer
113 views

Why are not validation accuracy and loss as smooth as train accuracy and loss?

I am training a modified VGG16 network for classification (adding 0.5 dropout after each of the last FC layers). In the following plot I am training for a small number of epochs as an example, and it ...
3
votes
4answers
3k views

How do I choose the optimal batch size?

Batch size is a term used in machine learning and refers to the number of training examples utilised in one iteration. The batch size can be one of three options: batch mode: where the batch ...
3
votes
1answer
90 views

Use cross-validation to train after model selection

I have been recently reading about model selection algorithms (for example to decide which value of the regularisation parameter or what size of a neural network to use, broadly hyper-parameters). ...
3
votes
2answers
66 views

How to actually teach the ANN the resulting weights of different training inputs?

I thought I have implemented the code (from scratch, no library) for an artificial neural network (first endeavour in the field). But I feel like I miss something very basic or obvious. To make it ...
3
votes
1answer
105 views

Are there independent evaluations of various major AI platforms?

Has anyone had a chance to tinker with multiple major AI platforms such as TensorFlow, Cognitive Talk, Quill etc... What are the strengths and weaknesses of different AI platforms? Comprehensive ...
3
votes
1answer
163 views

Does training happen during NEAT?

When one uses NEAT to evolve the best fitting network for a task, does training take place in each epoch as well? If I understand correctly, training is the adjustment of the weights of the neural ...
3
votes
1answer
127 views

How are LSTM's trained for text generation?

I've seen some articles about text generation using LSTMs (or GRUs) for text generation. Basically it seems you train them by folding them out, and putting a letter in each input. But say you trained ...
3
votes
1answer
165 views

Can we apply ANN to cryptography?

If a group of computers have identical ANN with exact same set of learning data and all have functionality of encryption and decryption, would there be any way for interceptors to interpret encrypted ...
3
votes
1answer
238 views

How close are we to having an AI that can play Magic: The Gathering objectively well?

With tools like open AI will we be able to teach an AI to build its own decks? build a deck from a limited pool? or draft? evaluate the power level of a card?
3
votes
1answer
31 views

Reinforcement learning with hints or reference model

In Reinforcement Learning, when I train a model, it comes up with its own set of solutions. For example, if I am training a robot to walk, it will come up with its own walking gait, such as this Deep ...
3
votes
1answer
70 views

How to design a recommendation system for shift swapping?

I need to design an algorithm such that it handles the request for shift swapping. The algorithm will recommend a list of people who are more likely to swap that shift with the person by analyzing ...
3
votes
1answer
103 views

Neural Network training beginner question

I have a question about the training sequence regarding Neural Network recognition. Let's say an image has 28*28 pixels, which leads to 784 Input Nodes with various greyscale values and 10 output ...