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Results tagged with neural-network
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user 69822
Artificial neural networks (ANN), are composed of 'neurons' - programming constructs that mimic the properties of biological neurons. A set of weighted connections between the neurons allows information to propagate through the network to solve artificial intelligence problems without the network designer having had a model of a real system.
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Supervised multiclass classification : is ANN a good idea ? or use other classifiers?
I have a problem deciding what to use since i'm just beginning to creating predictive models.
Let's say I have a training dataset with 5 or 6 features and a testing dataset. (With around 50k rows in …
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Neural network or other algorithms?
I have a regression problem, with a million rows or so, around 10-15 features.
What should work better on that particular setting? Neural network or regular regressors?
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Predicting a numeric variable from many numeric variables, how to choose a proper structure?
How much data do you have? this is a regression problem that doesn't require using neural networks, you can solve this by using much simpler algorithms ( SVM, Linear Regression , Tree-based regressors …
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Training an acoustic model for a speech-to-text engine
What are the steps for training an acoustic model? The format of the data (the audio) includes its length and other characteristics. If anyone could provide a simple example of how to train an acousti …
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Is it possible that a CNN has better accuracy than RNN in word classification?
CNN considers only the current input while RNN considers the current input and also the previously received inputs. It can memorize previous inputs due to its internal memory
Here's a comparative …
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What to use in setting up a Speech to Text engine in production?
So i have the task to study the feasability of setting up a Speech-To-Text engine in a production environnement, and i've been researching on this topic, so I tried Google's Speech-To-Text API and the …
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Football match prediction using regression
If your MSE is low, but then your predictions on the test set are way off, i can think only of over-fitting either you're leaking information from the training set to the test set ( or vice-versa ) or …
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Accepted
Predict using a saved regression model
Use sklearn.preprocessing.OneHotEncoder for example and transfer the one-hot encoding to your web-service ( i'm guessing that's how you're using the model for inference ) via sklearn.pipeline.Pipeline …
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in which case can I say that the data are bad and I ll achieve nothing using machine learnin...
Adding to the previous answer, you should know that using a reasonable number of features should give a score that is somewhat close to what it can give with optimal settings.
If your data is uninfo …
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A the end of a big DS project, should I make trained models available on GitHub?
From what I've seen on Github while looking for open source projects is that people usually do both.
You can have a section where one loads the models and runs the inference, and another section whe …
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