Tags
A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of da…
9834 questions
Use for data science questions related to the programming language Python. Not intended for general coding questions (-> stackoverflow).
5875 questions
a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hi…
4206 questions
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 informati…
3947 questions
An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.
2815 questions
Keras is a popular, open-source deep learning API for Python built on top of TensorFlow and is useful for fast implementation. Topics include efficient low-level tensor operations, computation of arbi…
2563 questions
Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human (natural) languages. As such, NLP…
2150 questions
scikit-learn is a popular machine learning package for Python that has simple and efficient tools for predictive data analysis. Topics include classification, regression, clustering, dimensionality re…
2005 questions
TensorFlow is an open source library for machine learning and machine intelligence. TensorFlow uses data flow graphs with tensors flowing along edges. For details, see https://www.tensorflow.org. Te…
1998 questions
Time series are data observed over time (either in continuous time or at discrete time periods).
1549 questions
R is a free, open-source programming language and software environment for statistical computing, bioinformatics, and graphics.
1370 questions
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
1321 questions
A dataset is a collection of data, often in tabular or matrix form.
This tag is NOT intended for data requests ("where can I find a dataset about ...") --> see OpenData
1286 questions
Convolutional Neural Networks (CNN, also called ConvNets) are a tool used for classification tasks and image recognition. The name giving first step is the extraction of features from the input data.…
1240 questions
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than t…
1238 questions
pandas is a python library for Panel Data manipulation and analysis, e.g. multidimensional time series and cross-sectional data sets commonly found in statistics, experimental science results, econome…
1134 questions
An activity that seeks patterns in large, complex data sets. It usually emphasizes algorithmic techniques, but may also involve any set of related skills, applications, or methodologies with that goal…
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Statistical techniques used for predicting outcomes.
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LSTM stands for Long Short-Term Memory. When we use this term most of the time we refer to a recurrent neural network or a block (part) of a bigger network.
1019 questions
Statistics is a scientific approach to inductive inference and prediction based on probabilistic models of the data. By extension, it covers the design of experiments and surveys to gather data for th…
960 questions
Methods and principles of selecting a subset of attributes for use in further modelling
842 questions
Random forest is a machine-learning classifier based on choosing random subsets of variables for each tree and using the most frequent tree output as the overall classification.
741 questions
Questions mostly concerned with managing data, without focus on pre-processing or modelling.
715 questions
For questions about image classification: a decision problem where an algorithm must decide to which class ('cat', 'chair', 'tree') an input image belongs.
690 questions
A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed cycle.
681 questions
A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one wa…
664 questions
Data cleaning is a preliminary step to statistical analysis in which the data-set is edited to correct errors and to put it into a form suitable for processing by statistical software.
641 questions
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
638 questions
A convolutional neural network is a form of neural network with an additional convolutional layer, typically used in image & audio analysis. The convolutional layer is essentially a filtering stage de…
637 questions
A machine learning model is a simplified representation of a dataset, derived from statistics in the data, used to make predictions. It can represent patterns, behaviours or features within this datas…
621 questions
Constructing meaningful and useful graphical representations of data. (If your question is only about how to get particular software to produce a specific effect, then it is likely not on topic here.)…
613 questions
For questions related to the eXtreme Gradient Boosting algorithm.
605 questions
Refers generally to statistical procedures that utilize the logistic function, most commonly various forms of logistic regression
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Area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.
556 questions
Training is the part of machine learning whereby a model is "trained" on a define portion of a dataset to learn attributes and statistical features of the data. It's counterparts are called Testing an…
553 questions
Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts …
553 questions