223 research outputs found
Neural Machine Translation
Neural Machine Translation is the primary algorithm used in industry to perform machine translation. This state-of-the-art algorithm is an application of deep learning in which massive datasets of translated sentences are used to train a model capable of translating between any two languages. The architecture behind neural machine translation is composed of two recurrent neural networks used together in tandem to create an Encoder Decoder structure. Attention mechanisms have recently been developed to further increase the accuracy of these models. In this senior thesis, the various parts of Neural Machine Translation are explored towards the eventual creation of a tutorial on the topic. In the first half of this paper, each of the aspects that go into creating a NMT model are explained in depth. With an understanding of the mechanics of NMT, the second portion of this paper briefly outlines enhancements that were made to the PyTorch tutorial on NMT to create an updated and more effective tutorial on the topic
Direct flow synthesis of H2O2 catalysed by palladium supported on sulfonated polystyrene resins
Partial alkyne reduction in flow:Adaptation of the lindlar protocol prompted by a flow synthesis of combretastatin A-4
Partial alkyne reduction in flow:Adaptation of the lindlar protocol prompted by a flow synthesis of combretastatin A-4
Synthesis, crystal structure and conformational analysis of an unexpected [1,5]dithiocine product of aminopyridine and thiovanillin
Reflections on and consequences of an authentic multilingual education in luxembourg
Counsellor of the Minister of Education (Luxembourg
A convergent strategy for the pamamycin macrodiolides:Total synthesis of pamamycin-607, pamamycin-593, and pamamycin-621D precursors
International audienc
Direct flow synthesis of H2O2 catalysed by palladium supported on sulfonated polystyrene resins
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