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Transfer learning (TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. For example, for image classification , knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.
The C# programming language was designed by Anders Hejlsberg from Microsoft in 2000 and was later approved as an international standard by Ecma (ECMA-334) in 2002 and ISO / IEC (ISO/IEC 23270 and 20619 [c]) in 2003. Microsoft introduced C# along with .NET Framework and Visual Studio, both of which were closed-source.
Domain adaptation is the ability to apply an algorithm trained in one or more "source domains" to a different (but related) "target domain". Domain adaptation is a subcategory of transfer learning. In domain adaptation, the source and target domains all have the same feature space (but different distributions); in contrast, transfer learning ...
Seq2seq. Seq2seq is a family of machine learning approaches used for natural language processing. [1] Applications include language translation, image captioning, conversational models, and text summarization. [2] Seq2seq uses sequence transformation: it turns one sequence into another sequence.
Natural language processing ( NLP) is an interdisciplinary subfield of computer science and information retrieval. It is primarily concerned with giving computers the ability to support and manipulate human language. It involves processing natural language datasets, such as text corpora or speech corpora, using either rule-based or ...
ML.NET is a free software machine learning library for the C# and F# programming languages. It also supports Python models when used together with NimbusML. The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks.
CS50 ( Computer Science 50) is an on-campus and online introductory course on computer science taught at Harvard University and Yale University. In 2016, CS50 became available to high school students as an Advanced Placement Computer Science course. The on-campus version is Harvard's largest class with 800 students, 102 staff, and up to 2,200 ...
v. t. e. Convolutional 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.