Data PreprocessingData preprocessing can refer to manipulation or dropping of data before it is used in order to ensure or enhance performance, and is an important step in the data mining process. The phrase "garbage in, garbage out" is particularly applicable to data mining and machine learning projects. Data collection methods are often loosely controlled, resulting in out-of-range values, impossible data combinations, and missing values, amongst other issues. Analyzing data that has not been carefully screened for such problems can produce misleading results.
Neural networkA neural network can refer to a neural circuit of biological neurons (sometimes also called a biological neural network), a network of artificial neurons or nodes in the case of an artificial neural network. Artificial neural networks are used for solving artificial intelligence (AI) problems; they model connections of biological neurons as weights between nodes. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed.
High German languagesThe High German languages (hochdeutsche Mundarten, i.e. High German dialects), or simply High German (Hochdeutsch) – not to be confused with Standard High German which is commonly also called "High German" – comprise the varieties of German spoken south of the Benrath and Uerdingen isoglosses in central and southern Germany, Austria, Liechtenstein, Switzerland, Luxembourg, and eastern Belgium, as well as in neighbouring portions of France (Alsace and northern Lorraine), Italy (South Tyrol), the Czech Republic (Bohemia), and Poland (Upper Silesia).
Standard GermanStandard High German (SHG), less precisely Standard German, or High German (Standardhochdeutsch, Standarddeutsch, Hochdeutsch or, in Switzerland, Schriftdeutsch) while referring to its regional origins and not to be confused with High German dialects, is the standardized variety of the German language used in formal contexts and for communication between different dialect areas. It is a pluricentric Dachsprache with three codified (or standardised) specific regional variants: German Standard German, Austrian Standard German and Swiss Standard German.
Descriptive statisticsA descriptive statistic (in the count noun sense) is a summary statistic that quantitatively describes or summarizes features from a collection of information, while descriptive statistics (in the mass noun sense) is the process of using and analysing those statistics. Descriptive statistics is distinguished from inferential statistics (or inductive statistics) by its aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent.
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and exploding gradients, seen during backpropagation in earlier neural networks, are prevented by using regularized weights over fewer connections. For example, for each neuron in the fully-connected layer 10,000 weights would be required for processing an image sized 100 × 100 pixels.
German diasporaThe German diaspora consists of German people and their descendants who live outside of Germany. The term is used in particular to refer to the aspects of migration of German speakers from Central Europe to different countries around the world. This definition describes the "German" term as a sociolinguistic group as opposed to the national one since the emigrant groups came from different regions with diverse cultural practices and different varieties of German.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Models of neural computationModels of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing in biological nervous systems, or functional components thereof. This article aims to provide an overview of the most definitive models of neuro-biological computation as well as the tools commonly used to construct and analyze them.
Text miningText mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al.
