In this post, I want to show how I use NLTK for preprocessing and tokenization, but then apply machine learning techniques (e.g. building a linear SVM using stochastic gradient descent) using Scikit-Learn.
@startuml
participant User
User -> A: DoWork
activate A #FFBBBB
A -> A: Internal call
activate A #DarkSalmon
A -> B: << createRequest >>
activate B
B --> A: RequestCreated
deactivate B
deactivate A
A -> User: Done
deactivate A
@enduml
Now you can easily create tables in plain text which can be copied into any text file. Multi-line cells' contents is supported as well as multirow and multicolumn spanning of cells.
This tutorial is inspired from classic vimtutor. You will get to learn some handy shortcuts to work with Sublime Text 3. By the end of this tutorial, you would be familiar with ST's most important and frequently used shortcuts and features.
Textuality is often thought of in linguistic terms; for instance, the talk and writing that circulate in the classroom. In this paper I take a multimodal perspective on textuality and context. I draw on illustrative examples from school Science and English to examine how image, colour, gesture, gaze, posture and movement—as well as writing and speech—are mobilized and orchestrated by teachers and students, and how this shapes learning contexts. Throughout the paper I discuss the issues raised by a multimodal perspective for the conceptualization of text and learning context, and how this approach can contribute to learning and pedagogy more generally. I suggest that attending to the full ensemble of communicative modes involved in learning contexts enables a richer view of the complex ways in which curriculum knowledge (and policy) is mediated and articulated through classroom practices.