Train a language model on a jokes corpus Train a character-level language model on a corpus of jokes. To do so, use this k English jokes dataset or build your own the larger the better; if you do so, please submit a pull request and we'll link to your datasetimplement a character-level LSTM or use an existing implementationtrain it on this dataset, and draw samples from it. If successful, the output from the LSTM should be actually funny.
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Summary: Elaborate usability tests are a waste of resources. The best results come from testing no more than 5 users and running as many small tests as you can afford. Some people think that usability is very costly and complex and that user tests should be reserved for the rare web design project with a huge budget and a lavish time schedule.
Requests for Research and to show that it can learn algorithmic tasks (such as bubble sort, quick sort, multiplication, various string operations, etc) quickly.
The code and an associated paper for a model implementing a version of the "Inverse DRAW" model is available here.
Quicksort is a fast sorting algorithm that takes a divide-and-conquer approach to sorting lists. While sorting is a simple concept, it is a basic principle used in complex programs such as file search, data compression, and pathfinding.
Running time is an important thing to consider when selecting a sorting algorithm since efficiency is often thought of in terms of speed. Abstract—In this paper we are proposing a new sorting algorithm, List Sort algorithm, is based on the dynamic memory allocation. In this research study we have also shown the comparison of various efficient sorting techniques with List sort.
algorithms which are based on comparison are Quick sort O(nlog 2 n), Heap sort O(nlog 2 n. Downloading a free research paper.
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