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1500 questions
28
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2 answers

What is the difference between cross_validate and cross_val_score?

I understand cross_validate and how it works, but now I am confused about what cross_val_score actually does. Can anyone give me some example?
Taimur Islam
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2 answers

Is there away to change the metric used by the Early Stopping callback in Keras?

When using the early stopping callback in Keras, training stops when some metric (usually validation loss) is not increasing. Is there a way to use another metric (like precision, recall, or f-measure) instead of validation loss? All the examples I…
P.Joseph
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28
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3 answers

Why convolutions always use odd-numbers as filter size

If we have a look to 90-99% of the papers published using a CNN (ConvNet). The vast majority of them use filter size of odd numbers:{1, 3, 5, 7} for the most used. This situation can lead to some problem: With these filter sizes, usually the…
Jonathan DEKHTIAR
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3 answers

What is weight and bias in deep learning?

I'm starting to learn Machine learning from Tensorflow website. I have developed a very very rudimentary understanding of the flow a deep learning program follows (this method makes me learn fast instead of reading books and big articles). There…
Umer Farooq
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28
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1 answer

PyTorch vs. Tensorflow Fold

Both PyTorch and Tensorflow Fold are deep learning frameworks meant to deal with situations where the input data has non-uniform length or dimensions (that is, situations where dynamic graphs are useful or needed). I would like to know how they…
noe
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28
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5 answers

What is the benefit of splitting tfrecord file into shards?

I'm working on speech recognition with Tensorflow and plan to train LSTM NN with massive waves dataset. Because of the performance gains, I plan to use tfrecords. There are several examples on internet (Inception for ex.) where tfrecords files are…
striki70
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28
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3 answers

Why are NLP and Machine Learning communities interested in deep learning?

I hope you can help me, as I have some questions on this topic. I'm new in the field of deep learning, and while I did some tutorials, I can't relate or distinguish concepts from one another.
user3352632
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28
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6 answers

Machine learning techniques for estimating users' age based on Facebook sites they like

I have a database from my Facebook application and I am trying to use machine learning to estimate users' age based on what Facebook sites they like. There are three crucial characteristics of my database: the age distribution in my training set…
Wojciech Walczak
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28
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4 answers

Any "rules of thumb" on number of features versus number of instances? (small data sets)

I am wondering, if there are any heuristics on number of features versus number of observations. Obviously, if a number of features is equal to the number of observations, the model will overfit. By using sparse methods (LASSO, elastic net) we can…
Arnold Klein
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28
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5 answers

Improve the speed of t-sne implementation in python for huge data

I would like to do dimensionality reduction on nearly 1 million vectors each with 200 dimensions(doc2vec). I am using TSNE implementation from sklearn.manifold module for it and the major problem is time complexity. Even with method = barnes_hut,…
chmodsss
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27
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5 answers

Python library for segmented regression (a.k.a. piecewise regression)

I am looking for a Python library that can perform segmented regression (a.k.a. piecewise regression). Example:
Franck Dernoncourt
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27
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5 answers

BERT vs Word2VEC: Is bert disambiguating the meaning of the word vector?

Word2vec: Word2vec provides a vector for each token/word and those vectors encode the meaning of the word. Although those vectors are not human interpretable, the meaning of the vectors are understandable/interpretable by comparing with other…
sovon
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27
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2 answers

What is the difference between semantic segmentation, object detection and instance segmentation?

I'm fairly new at computer vision and I've read an explanation at a medium post, however it still isn't clear for me how they truly differ.
Guilherme Marques
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27
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4 answers

Word2Vec for Named Entity Recognition

I'm looking to use google's word2vec implementation to build a named entity recognition system. I've heard that recursive neural nets with back propagation through structure are well suited for named entity recognition tasks, but I've been unable…
Madison May
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2 answers

How to deal with time series which change in seasonality or other patterns?

Background I'm working on a time series data set of energy meter readings. The length of the series varies by meter - for some I have several years, others only a few months, etc. Many display significant seasonality, and often multiple layers -…
Jo Douglass
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