In computer science, the list-labeling problem involves maintaining a totally ordered set S supporting the following operations: * insert(X), which inserts X into set S; * delete(X), which removes X from set S; * label(X), which returns a label assigned to X subject to: * label(X) * X,Y S, X < Y implies label(X) < label(Y) The cost of a list labeling algorithm is the number of label (re-)assignments per insertion or deletion. List labeling algorithms have applications in many areas, including the order-maintenance problem, , data structure persistence, graph algorithms and fault-tolerant data structures. Sometimes the list labeling problem is presented where S is not a set of values but rather a set of objects subject to a total order. In this setting, when an item is inserted into S, it is specified to be the successor of some other item already in S. For example, this is the way that list labeling is used in the order-maintenance problem. The solutions presented below apply to both formulations. (Wikipedia).
Python Programming 11. Introduction to Lists
This is the 11th in a course of computer science video lessons introducing programming with Python. This video introduces the list data structure. A list is a convenient way to store a group of data items which are usually related in some way. A list is an alternative to using several s
From playlist Python Programming Step by Step
HTML Ordered and Unordered Lists
In this HTML video, you’ll learn about ordered and unordered lists. They help to organize text on a webpage into numbered and bulleted lists. We hope you enjoy! To learn more, check out our Basic HTML tutorial here: https://edu.gcfglobal.org/en/basic-html/ #html #orderedlists #unordered
From playlist HTML
See complete series on data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P In this lesson, we have described linked list data structure. We have analyzed our limitations with array data structure and tried to understand the need for linked list. F
From playlist Data structures
Linked List Data Structure 1. Representation and Traversal (algorithms and pseudocode).
This is the first in a series of videos about the linked list data structure. It mentions the applications of linked lists, and describes how a linked list can be represented programmatically using a Data array and an array of Next pointers. It also includes pseudocode for traversing, an
From playlist Data Structures
[c] Introduction to Linked Lists
From playlist Data Structures
Scheduling: The List Processing Algorithm Part 1
This lesson explains and provides an example of the list processing algorithm to make a schedule given a priority list. Site: http://mathispower4u.com
From playlist Scheduling
In this Wordpress Video Tutorial you'll find out everything you ever wanted to know about Wordpress Taxonomies and more. A Taxonomy is just a fancy word that represents a way you can better sort your posts, pages and links in Wordpress. Code is Here: http://goo.gl/Pg2wH
From playlist Wordpress Theme Tutorial
Data Structures: List as abstract data type
See complete series of videos in data structures here: http://www.youtube.com/playlist?list=PL2_aWCzGMAwI3W_JlcBbtYTwiQSsOTa6P&feature=view_all In this lesson, we will introduce a dynamic list structure as an abstract data type and then see one possible implementation of dynamic list using
From playlist Data structures
1.3 Creating lists in Python | functions | Tutorial course in data science and Statistical analysis
In this episode in the crash course tutorial of statistics and data science with Python we'll discuss the creating and manipulation of lists in Python Additionally, we discuss among others: -. What is a list? why is it so important? -. What is a list and what are its properties -. How to
From playlist Python
Live CEOing Ep 603: Language Design in Wolfram Language [Rank, PositionCases & Operator Forms]
In this episode of Live CEOing, Stephen Wolfram discusses upcoming improvements and features to the Wolfram Language. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram
From playlist Behind the Scenes in Real-Life Software Design
Building Robust Machine Learning Models from Noisy Labeled Data
Many machine learning (ML) models operating in big and small enterprises are often trained on noisy, crowdsourced, or user-generated data. As the annotators are not experts in the application domain or data labeling, ML specialists have to take this property into account when training and
From playlist Advanced Machine Learning
Live CEOing Ep 264: Language Design in Wolfram Language
Watch Stephen Wolfram and teams of developers in a live, working, language design meeting. This episode is about Language Design in the Wolfram Language.
From playlist Behind the Scenes in Real-Life Software Design
Preparing and Labeling Data for Binary Text Classification (Neural Networks for DH 11b)
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From playlist Binary Text Classification (Dan Brown v. Oscar Wilde)
Weak Supervision NLP with spaCy and Skweak
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From playlist SpaCy for Digital Humanities with Python Tutorials
From playlist Machine Learning Course
Rasa Livecoding: Dialect bot (Exporting trained models from Jupyter, Part 2)
Welcome to Rasa livecoding with Rachael! In this episode, we'll continue exporting the trained classifier model out of a Jupyter notebook & into a custom action to use with our assistant. What's livecoding? It's folks working on real projects in real time with help from you, the audience
From playlist Live Coding
Live CEOing Ep 609: Language Design in Wolfram Language [Minimal Tree Design, DisjointQ & More]
In this episode of Live CEOing, Stephen Wolfram discusses upcoming improvements and features to the Wolfram Language. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram
From playlist Behind the Scenes in Real-Life Software Design
Python In Education: Advanced 2D Plots
This video describes a few advanced methods for making plots using Python and Matplotlib. Here, I cover: * points and lines on the same plot * logarithmic plots (log-linear) * error bars (both y and x error bars) * bar graphs (including stacked bar graphs) * colored background and grids
From playlist Python In Education
Live CEOing Ep 542: Language Design in Wolfram Language [GraphThemes]
In this episode of Live CEOing, Stephen Wolfram discusses upcoming improvements and features to the Wolfram Language. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram
From playlist Behind the Scenes in Real-Life Software Design
Heaps Of Fun Solution - Intro to Algorithms
This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.
From playlist Introduction to Algorithms