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.

Image preprocessing are the steps taken to format images before they are used by model training and inference. This includes, resizing, orienting, and color corrections. Preprocessing is required t…
151 questions
Graphics Processing Units (GPUs) within the context of Machine Learning often refer to the hardware requirements, design considerations, or level of parallelization for implementing and running variou…
150 questions
Activation function is a non-linear transformation, usually applied in neural networks to the output of the linear or convolutional layer. Common activation functions: sigmoid, tanh, ReLU, etc.
147 questions
Text is a type of data often used in data science projects involving natural language processing.
145 questions
For questions which concern getting started in Data Science or any of its related subdomains.
138 questions
Jupyter is a collection of environments and protocols for interactive computing. It supports many languages and kernels, and works with frontends including the web application Jupyter Notebook. Jupyte…
136 questions
Use for questions about graphing a dataset into a visualisation (e.g. line plot, histogram or pie chart). Visualisation and plotting is an important EDA tool as well as presenting the results of a dat…
134 questions
NLTK is a free, open-source natural language processing toolkit for python. It is used primarily for text processing applications and includes libraries specifically made for classification, tokenizat…
133 questions
For question regarding distance between distributions or variables, such as Euclidean distance between points in n-space.
132 questions
Hyperparameters of a model are the kind of parameters that cannot be directly learned during training but are set beforehand. Hyperparameters can define, for example, the complexity of the model or it…
132 questions
A topic model describes text from a large corpus as a probability distribution over topics which are probability distributions over words. There are quantified contributions from all topics to a speci…
130 questions
A model-free reinforcement learning technique.
128 questions
For questions about models designed for generating new data (or generating samples from a probability distribution).
121 questions
Hadoop is an Apache open-source project that provides software for reliable and scalable distributed computing. The project itself includes a variety of other complementary additions.
118 questions
Latent Dirichlet Allocation (LDA) is an algorithm in the field of topic modeling.
117 questions
Information Retrieval is an area of study concerning with retrieving documents, information or metadata from a collection of unstructured or semi-structured data.
117 questions
Kaggle is an online community for data scientists and machine learning practitioners owned by Google.
116 questions
The Spark Python API (PySpark) exposes the apache-spark programming model to Python.
116 questions
tf–idf (term frequency–inverse document frequency), is a numerical statistic using in nlp that is intended to reflect how important a word is to a document in a collection or corpus. It is often used…
110 questions
Bayesian statistics is a statistical paradigm that contrasts with that of frequentist statistics. Bayesian methods rely on prior information do determine the degree of belief in the probability of a v…
103 questions
Ranking is ordering data from highest to lowest or *vice versa.* For questions about *constructing* scores to use in ranking, please use the "valuation" tag, too.
100 questions
In machine learning, grid search refers to multiple runs to find the optimal value of parameter(s)/hyperparameter(s) of a model, e.g. mtry for random-forest or alpha, beta, lambda for glm, or C, kerne…
99 questions
98 questions
Data imputation is the process of replacing missing data with substituted values. This could involve statistically representative data filling (e.g. local averages) or simply replacing the missing dat…
98 questions
gensim is the python library for topic modelling. multi-dimensional vector representation of words or sentences which preserves semantic meaning is computed through word2vec and doc2vec models.
98 questions
Use for questions about the labels associated with the ground-truth of a dataset. Typically these data points have been labelled by a domain expert and can therefore be assumed to be true, against whi…
93 questions
1 2 3