Data types | Unary operations | Type theory

Type conversion

In computer science, type conversion, type casting, type coercion, and type juggling are different ways of changing an expression from one data type to another. An example would be the conversion of an integer value into a floating point value or its textual representation as a string, and vice versa. Type conversions can take advantage of certain features of type hierarchies or data representations. Two important aspects of a type conversion are whether it happens implicitly (automatically) or explicitly, and whether the underlying data representation is converted from one representation into another, or a given representation is merely reinterpreted as the representation of another data type. In general, both primitive and compound data types can be converted. Each programming language has its own rules on how types can be converted. Languages with strong typing typically do little implicit conversion and discourage the reinterpretation of representations, while languages with weak typing perform many implicit conversions between data types. Weak typing language often allow forcing the compiler to arbitrarily interpret a data item as having different representations—this can be a non-obvious programming error, or a technical method to directly deal with underlying hardware. In most languages, the word coercion is used to denote an implicit conversion, either during compilation or during run time. For example, in an expression mixing integer and floating point numbers (like 5 + 0.1), the compiler will automatically convert integer representation into floating point representation so fractions are not lost. Explicit type conversions are either indicated by writing additional code (e.g. adding type identifiers or calling built-in routines) or by coding conversion routines for the compiler to use when it otherwise would halt with a type mismatch. In most ALGOL-like languages, such as Pascal, Modula-2, Ada and Delphi, conversion and casting are distinctly different concepts. In these languages, conversion refers to either implicitly or explicitly changing a value from one data type storage format to another, e.g. a 16-bit integer to a 32-bit integer. The storage needs may change as a result of the conversion, including a possible loss of precision or truncation. The word cast, on the other hand, refers to explicitly changing the interpretation of the bit pattern representing a value from one type to another. For example, 32 contiguous bits may be treated as an array of 32 booleans, a 4-byte string, an unsigned 32-bit integer or an IEEE single precision floating point value. Because the stored bits are never changed, the programmer must know low level details such as representation format, byte order, and alignment needs, to meaningfully cast. In the C family of languages and ALGOL 68, the word cast typically refers to an explicit type conversion (as opposed to an implicit conversion), causing some ambiguity about whether this is a re-interpretation of a bit-pattern or a real data representation conversion. More important is the multitude of ways and rules that apply to what data type (or class) is located by a pointer and how a pointer may be adjusted by the compiler in cases like object (class) inheritance. (Wikipedia).

Video thumbnail

C Programming Tutorial - 11: Type Conversion in C

In this tutorial we'll learn how C perform implicit type conversion on values. The floating point values get demoted to integer values and the integer values get promoted to floating point values.

From playlist The Bad Tutorials: C Programming

Video thumbnail

Conversational AI with Rasa 2.x: Slots

*NOTE* this video is designed for Rasa 2.x. If you're looking for content for Rasa 3.x then you'll want to watch the updated version found here: https://www.youtube.com/watch?v=vNBHzSLZukc&list=PL75e0qA87dlEjGAc9j9v3a5h1mxI2Z9fi&index=7 In this episode of Conversational AI with Rasa, Just

From playlist Conversational AI with Rasa Open Source 2.x

Video thumbnail

Chatbot Memory for Chat-GPT, Davinci + other LLMs - LangChain #4

Conversational memory is how a chatbot can respond to multiple queries in a chat-like manner. It enables a coherent conversation, and without it, every query would be treated as an entirely independent input without considering past interactions. The memory allows a Large Language Model (

From playlist Recommended

Video thumbnail

Conversational AI with Rasa: Slots

In this episode of Conversational AI with Rasa, Justina Petraitytė will cover how your chatbot's memory works: slots are used to store values over the course of a conversation. This video will cover the different types of slots, how they're set, and how to have them influence the conversat

From playlist Conversational AI with Rasa Open Source 3.x

Video thumbnail

Interpreter Design Pattern

Code is Here: http://goo.gl/41GCs Welcome to my Interpreter Design Pattern Tutorial! The Interpreter design pattern is ignored by most, but in this tutorial I'll show you how to do some cool things with it. In top of that, I'll also answer all of the recent questions I've received about

From playlist Java Video Tutorial

Video thumbnail

The Typology of the Spoken Genres | Part 1

In this video, I discuss spoken genres. The topics discussed include miro-analysis of spoken genre (e.g., turn taking, turn-constructional units, transition relevance place, etc.) and conversation structures (e.g., transactions vs interactions). I recommend watching the following videos:

From playlist Spoken Genres

Video thumbnail

The Future of Conversational Experience

There has been a renaissance in conversational interfaces over the last few years. More and more businesses are using bots with interfaces that emulate human to human conversations to meet the needs of their customers, with some believing that conversations are going to eventually become t

From playlist Machine Learning

Video thumbnail

Going beyond “Sorry, I didn’t get that” building AI assistants that scale... - Justina Petraitytė

PyData DC 2018 Going beyond “Sorry, I didn’t get that”: building AI assistants that scale using machine learning In this workshop, you will get hands-on experience in developing intelligent AI assistants based entirely on machine learning and using only open source tools - Rasa NLU and R

From playlist Rasa: Open Source Conversational AI

Video thumbnail

Machine Learning at Uber (Natural Language Processing Use Cases)

At Uber, we are using natural language processing and conversational AI to improve the user experience. In my talk I will be delving into 2 use cases. In the first application we use natural language processing and machine learning to improve our customer care. The other use case is the re

From playlist Machine Learning

Video thumbnail

Conversation Analysis Theory in Chatbots | Michael Szul

Presented by Michael Szul, Manager of Undergraduate Medical Education Applications, UVA Health Rasa's Level 3 AI Assistant Conference (https://www.l3-ai.dev/).

From playlist Level 3 AI Assistant Conference 2020

Video thumbnail

How To Set Up Goals In Google Analytics 2021 | Google Analytics Advanced | Simplilearn

This video on how to set up goals in google analytics explains how to collect data to measure business goals in Google Analytics. Understand the process of setting up and configure Google Analytics goals in order to track necessary actions on your site. Google Analytics is a web analytics

From playlist Digital Marketing Playlist [2023 Updated]🔥 | Digital Marketing Course | Digital Marketing Tutorial For Beginners | Simplilearn

Related pages

IEEE 754 | Arithmetic logic unit | Data type | Eiffel (programming language) | Subtyping | Unintended consequences | Truncation | Aliasing (computing) | Variable (computer science) | Primitive data type | Integer (computer science) | String (computer science) | Run-time type information