OpenLLM-France/wikimedia huggingface dataset:
# Big Data/Spark

Apache Spark is a engine for large-scale data processing. It is optimized for the execution of multiple parallel operations on the same data set as they occur in many iterative machine learning tasks.
In Spark, data is stored as resilient distributed datasets (RDDs), i.e., an immutable, persistent set of objects that is partitioned across several computers. Two types of operations are defined on RDDs:
* Transformations: RDD x Function -> RDD apply a function on an RDD and create a new RDD
* Actions: RDD x Function -> Object compute a result from an RDD
These operations are executed lazily. This means that Spark stores the sequence of operations performed on an RDD. These operations are only executed, if (i) an action is performed and a result has to be computed or (ii) the computation of an RDD is explicitly requested.
The execution of a Spark application starts with the driver program. It acquires resources from an external cluster management system like YARN and instructs it to start the processes of the application.

## Additional APIs

Newer versions of Spark include high level APIs for dealing with data, including Spark SQL, Spark DataFrames and Datasets (Datasets does not currently support Python). These APIs include additional information beyond what is provided in the RDD to enable "extra optimizations".
# Big Data/Sidebar

Resembles a side bar for Big Data. Most content comes from the Big Data/Navigation page.
# Big Data/Titan Graph

Aurelius Titan Graph is a graph database that can be set on top of distributed stores like Apache Cassandra or Apache HBase.

## Related Technologies

* Big Data/Cassandra
* Big Data/HBase
# Big Data/MonetDB

MonetDB is a column-store, i.e., for each column in a relational table a binary association table (BAT) is created that maps an object identifier to the corresponding value. It exploits the main memory but the database is still persisted on disk. MonetDB can be used as a distributed database. Its design focusses on a read-dominated workload and updates consist of appending large data chunks at a time.
MonetDB consists of three layers:

## Front-end

    provides the user-level data model and the query languages SQL, XQuery (for XML), SciQL (for arrays) and SPARQL (for RDF).
    First, the query is translated into relational algebra. Then, a domain-specific strategic optimization is applied, which tries to reduce the amount of data to be processed. The resulting optimization plan is finally translated into the MonetDB Assembly Language (MAL).

## Back-end

    consists of the MAL optimizer and interpreter.
    The performed tactical optimization is inspired by programming language optimization and ranges from symbolic processing up to just-in-time data distribution and execution.

## Kernel

    provides BATs and a library of optimized implementations of the binary relational algebra operators.
    The operational optimization chooses at runtime the optimal algorithm and implementation to perform the defined operators on the used input data.

## MonetDB/RDF

RDF triples consist of three object identifiers: S (Subject), P (Property) and O (Object). Each triple is stored in six triple tables: SPO, SOP, PSO, POS, OPS and OSP. This leads to 18 BATs. Before inserting a triple into the database, a dictionary module decomposes an URI into the largest common prefix, which is stored only once, and the unique ID of a subject, property or object.
Current research: Use characteristic sets (CS) to derive relational tables. For each subject in a (CS) an own table is formed. Each column represents a property and the values the corresponding objects. An object which is another subject is expressed via a foreign key. Irregular triples (belonging to no CS are stored separately in a basic triple storage. The relational schema should adapt during runtime.
In order to reduce the number of CSs, attributes of king 0..n are allowed. Since a column of MonetDB must be exactly of one type, for each distinct object type of one property an own CS is created. Furthermore, a schema fine-tuning like the unification of 1..1 related CSs.
# Big Data/Redis DataBase

Redis is an open-source in-memory database project implementing a distributed, in-memory key-value store with optional durability. Redis supports different kinds of abstract data structures, such as strings, lists, maps, sets, sorted sets, hyperloglogs, bitmaps and spatial indexes.
Redis is also provided as a service in different Cloud providers ElastiCache from Amazon Web Services and Azure Cache from Microsoft Azure.

## Basic commands

* Connect to Redis database:
* Get a list of keys: redis-cli --scan
* Get redis information:

## Redis Enterprise

Redis Enterprise is a commercial version of Redis including replication capabilities.
K8s operator for Redis Enterprise was released in October 2018.
CRDB (Conflict-free Replicated Redis Database) allows to run an application in a distributed manner across cloud and on-prem.

## Activities

* Read Redis release Notes https://raw.githubusercontent.com/antirez/redis/5.0/00-RELEASENOTES
# Big Data/Navigation

This side contains all technologies and sub-topics. For the navigational part, we split it from the Sidebar and the Main page. Can also be useful for referencing somewhere else.

## Technologies

* Distributed Files Sstem
** Google File System
** Apache HDFS
* Distributed Programming
** MapReduce
** Apache Pig
** Apache Spark
** Apache Tez
* NoSQL Databases
** Column Data Model
*** Google BigTable
*** Apache HBase
*** Hypertable
*** Amazon Dynamo
*** Apache Cassandra
*** Apache Accumulo
*** MonetDB
** Document Data Model
*** MongoDB
** Key-value Data Model
*** Redis DataBase
*** OpenTSDB
** Graph Data Model
*** Aurelius Titan Graph
** Data Grid
*** Hazelcast
* NewSQL Databases
** Google Spanner
* RDF Stores
** CumulusRDF
* SQL-on-Hadoop
** Apache Hive
** Google Dremel
** Apache Drill
** Cloudera Impala
** Apache Spark SQL
** AMPLAB Shark
* Service Programming
** Apache YARN
** Apache Thrift
** Apache Zookeeper
* Stream Processing
** Apache Storm
** Apache S4
** Apache Spark Streaming
** Google MillWheel
* Graph Processing
** Google Pregel
** Apache Giraph
** Apache Spark GraphX
* Cloud Services
** Amazon EMR
# Big Data/Pig

Apache Pig provides a high-level declarative query language for Hadoop MapReduce.
Pig provides the query language Pig Latin. A Pig Latin script specifies a sequence of steps. Each steps defined only a single, high-level data transformation. When executing this script, it is first transformed into a logical plan that describes its execution. This plan is used to compile several MapReduce jobs that are executed on the Hadoop cluster.
Additional features:
* user defined functions as first-class citizens
* arbitrary input and output file formats
* nested data model
Main operations:
* LOAD
* FOREACH
* FILTER
* COGROUP
* GROUP
* JOIN
* UNION
* CROSS
* ORDER
* DISTINCT
* STORE
# Big Data/SparkStreaming

Apache Spark Streaming is the streaming extension of Apache Spark.
The basic idea is buffer the data of a continuously arriving data stream for a certain amount of time. The resulting data stream segments are processed by Spark as usual. The resulting intermediate results are combined by applying specific operations like union.
# Formal language theory

A formal language is a set of strings over a finite alphabet. Formal language theory is the study of formal languages, or often more accurately the study of families of formal languages. It deals with hierarchies of language families defined in a wide variety of ways. Formal language theory is concerned with the purely syntactical aspects, rather than a semantics or meaning of the strings.
It is closely related to automata theory, which deals with formally defined machines that accept (or generate, according to the viewpoint) formal languages.
It is also related to complexity theory, because once a formal system capable of universal computation is fixed, a computational problem is nothing but a formal language containing all the descriptions of problem instances, and the answer to the problem is the subset of instances that would be accepted (could be derived) -- which need not be effective, and need not be a computable set, of course.

## Preliminaries

The free monoid $(\Sigma ^{*},\cdot )$ over a finite set $\Sigma$ is the set of finite strings whose letters are in the alphabet $\Sigma$, together with the basic operation of concatenation $\cdot :\Sigma ^{*}\times \Sigma ^{*}\rightarrow \Sigma ^{*}$, which puts two strings together. $\Sigma ^{*}$ contains the empty word, written as $\epsilon$ or $\lambda$. Languages may be finite or infinite ($\Sigma ^{*}$ itself is a language containing all possible words over $\Sigma$, whilst $\{o,lo,llo,ello,hello\}$ is a finite language), but contain only finite words.

## Hierarchies

One is often interested in establishing hierarchies of language families. This is often much easier than in the field of computational complexity theory, since the languages of a family often share some structural property that allows one to pinpoint the difference between two families.
Hierarchies you might want to know about include the (extended) Chomsky hierarchy. It originates with the linguist Noam Chomsky, who sought to classify syntactic phenomena in natural languages.
The classes described therein are now basic to formal language theory because they have many equivalent definitions and many of their properties are well known.

## Planned Subjects

* Generators and acceptors
* Operations and closure properties
* Regular and context-free languages
* Abstract families of languages (AFL) theory
* Parallel replacement systems
* Complexity of parsing
* Decidability of certain questions
* Beyond ordinary words
* Some applications

## Extensions

Topics closely related to formal language theory are the study of infinite words, labeled partial orders, the study of graph languages, formal power series. Some of these subjects have a history of their own, but all include as a special case the case of ordinary word languages. Also, infinite alphabets have found applications.

## Applications
### Outside of computer science

Formal language theory finds uses outside of computer science and can also be of use to group theorists, for instance, when studying finitely generated groups.

## Further Reading

Hopcroft and Ullman (the original version)
# Form for a Bill of Pains and Penalties
## Form

Preamble.
Whereas, on the ... day of ..., 19XX, A, then member of the House of Commons for the constituency of B, was complicit in the passing of the Bill for the XYZ Act 19XX by that House:
[The normal words of enactment go here]
Conviction, penalty and citation.
1.-(1) The said complicity of the said A in the said passing of the said Bill shall be deemed and adjudged high treason. (2) The said A shall be imprisoned for life. (3) This Act may be cited as the Punishment of A Act 20XX.
# Introduction the the Psychomotor Domain/Stages
## 4 satge of the Psychomotor Domain

4 stages in the development of the psychomotor skills include:
1. x
2. x
3. x
4. x
| Pyschomotor Domain | Pyschomotor Domain | < Back | Next > |
# Introduction to Abstract Algebra

* Introduction to Abstract Algebra
* An introductory course from the School of Mathematics
* Course Overview
* The main topic of the course is to introduce students to Group Theory, including the Sylow theorem. We'll also cover the structure of abelian groups and various permutation groups. If we have time, I'll also give a brief introduction to rings and fields including polynomial rings, factorization, the classical geometric constructions, and Galois theory.
* Course requirements
* The following knowledge is required or desirable on commencement of study of this course:
* School of Mathematics:Introduction to Proofs
* Linear Algebra
* Course outline
* We're going to follow a number of different sources for ths course. Primarily, we will follow Wikibooks' Abstract Algebra textbook. A good textbook to pick up is Topics in Algebra by I.N. Herstein. Another is Abstract Algebra by W.E. Deskins.
* Set Theory, Mappings and some Number Theory
* Introduction to Groups
* Subgroups
* Cosets
* The Lagrange Theorem
* Normal Subgroups
* Homomorphisms
* Automorphisms
* Cayley's Theorem
* Permutation Groups and Class Equations
* Sylow's Theorem
* Direct Products
* Intro to Rings, Fields and Galois Theory
* I will not assign grades unless you ask me to. If you would like to have your work graded, your grade will be the best of weighted averages of the three exams.
* Lecture series
* Lecture 1 - Introduction/Set Theory
* Lecture 2 - Relations and Mappings
* Lecture 3 - Groups
* Assignments
* Problem sets will be posted here after every lecture. These problem sets are designed to prepare the student for the exams. These will not be graded.
* Problem Set #1
* Problem Set #2
* Problem Set #3
* Examinations
* The plan is to have two 'midterm' exams and a comprehensive 'final' exam. Exam questions will be based on questions from the problem sets and the lectures. I'm debating on how to implement the exams, more information will be available soon. More than likely a link to the exam will be posted here, and you will post the answers on your user page or other page.
* Recommended student evaluation scheme
* not available yet
* Sign Up List
* If you are interested in taking this course, please indicate so here.
* Off-site lectures
* With video
* Verity Seeker, Basic abstract algebra, Youtube.
* Benedict Gross, Abstract Algebra, Open Learning Initiative, Harvard University Extension School.
* Bob Donley, Abstract Algebra, Math Doctor Bob, Youtube
* Without video
* Scott Williams, Introduction to Abstract Algebra, University of Arizona, Fall 2013.
* Reading
* Wikibooks: Abstract Algebra
* Thomas W. Judson, Abstract Algebra: Theory and Applications
* Samir Siksek, Lecture Notes, Introduction to Abstract Algebra, Mathematics Institute, University of Warwick -- Also see associated homework sets, listed under the appropriate section here.
# Korean/Words/Romanization
## Romanization
### ㅎㅏㄴㄱㅡㄹ

| ㅎ | ㅏ | ㄴ | ㄱ | ㅡ | ㄹ |
| h | a | n | g | eu | l |

### Hangul

Koreans may believe that Hangul is ideal. But it is quite defective in fact. Above all, long and short vowels are unsaid.
* Maybe not best
** No difference from long and short vowels.

### 한글 과 한국

| Vowels | short | long |
| 한글 | hangeul | harngeul |
| 한국 | hangug | harngug |

### Arae-a

ː Arae-a (아래아)
The Revised Romanization of Korean (RR) does little justice to old Korean language.

#### Readability

* ㄱ 기 깃
* ㄲ 끼 낏
* ㄴ 니 닛
* ㄷ 디 딧
* ㄸ 띠 띳
* ㄹ 리 릿
* ㅁ 미 밋
* ㅂ 비 빗
* ㅃ 삐 삣
* ㅅ 시 싯
* ㅆ 씨 씻
* ㅇ 이 잇
* ㅈ 지 짓
* ㅊ 치 칫
* ㅋ 키 킷
* ㅌ 티 팃
* ㅍ 피 핏
* ㅎ 히 힛

### Short and long vowels

| Hangul | Long vowel | Short vowel |
| 자기 | (jagi) self | (jargi) magnetism |
| 저자 | (jeja) market | (jerja) author |
| 종 | (jong) bell | (jorng) serf |
| 중 | (jung) middle | (jurng) monk |
| 징 | (jing) hobnail | (jirng) gong |

### Homonyms

English planer and planar are homonyms.
# Korean/Words/Xternals
## Manfred Kochen

    # Death Manfred Kochen
* GOOGLE AND THE CULTURE OF SEARCH
    Ken Hillis, Michael Petit, and Kylie Jarrett
    https://books.google.co.kr/books?id=0X_1HS13FbsC&pg=PA223&lpg=PA223&dq=Death+Manfred+Kochen&source=bl&ots=T7tWXi3k6Q&sig=ACfU3U0xbiyXBYRyb4ND6O1Y-_SP161clQ&hl=ko&sa=X&ved=2ahUKEwje3KnKl5vjAhXVP3AKHXcjCFMQ6AEwCXoECAUQAQ#v=onepage&q=Death%20Manfred%20Kochen&f=false

## Robert M. Young

w: Robert M. Young (academic)
http://www.psychoanalysis-and-therapy.com/human_nature/human/ackn.html
http://www.psychoanalysis-and-therapy.com/psychoanalytic_writings/books.html
http://www.psychoanalysis-and-therapy.com/psychoanalytic_writings/index.html
http://www.psychoanalysis-and-therapy.com/rmyoung/pubs.html
    COMMENTS ON THE WORK AND INFLUENCE OF ROBERT M. YOUNG

## Alan Turing

https://en.wikipedia.org/wiki/Alan_Turing
https://www.bbc.com/news/business-48962557
    New face of the Bank of England's £50 note is revealed as Alan Turing

## Michael Polanyi

    Michael Polanyi and His Generation: Origins of the Social Construction of Science
    w:Mary Jo Nye, University of Chicago Press, 2011-9-16. (432pp.)
The author reviews the role Michael Polanyi and some of his contemporaries played in the social turn in the philosophy of science. This turn was to see science as a struggle to overcome both empiricism and rationalism by attending to social communities, behavioral norms, and personal commitments. She argues that the roots of that social turn are to be found in the scientific and political context of Europe in the 1930s, when many scientists specially attended to the universal nature of scientific knowledge as a tool to fight against economic catastrophe, Stalinism and Fascism, to apply science to industry and social welfare. Polanyi was central here, Nye contends, as one of the first advocates of this new role of science. Nye reviews Polanyi’s scientific and political plays in Budapest, Berlin, and Manchester from 1910s to 1950s, and shows how he and his contemporaries, such as J. D. Bernal, Ludwik Fleck, Karl Mannheim, Robert K. Merton, and at last Thomas Kuhn, forged a politically charged philosophy of science, newly emphasizing the social role of science.
https://books.google.co.kr/books?id=7CLTNAzcynMC&dq=%22In+science+men+have+learned+consciously+to+subordinate+themselves+to+a+common+purpose+without+losing+the+individuality+of+their+achievements.+Each+one+knows+that+his+work+depends+on+that+of+his+predecessors+and+colleagues,+and+that+it+can+only+reach+its+fruition+through+the+work+of+his+successors.%22&hl=ko&source=gbs_navlinks_s

## Eugene Garfield

https://en.wikipedia.org/wiki/Talk:Eugene_Garfield
# Introduction to physics/lecture/Current and resistance
## The Relationship between Current and Resistance

Current and resistance are both related with the equation;
    $V={I\cdot R}\,$
(Where V is voltage, I is current and R is resistance.) Current is measured in Amps which is the amount of electric charge (in Coulombs) per second, and Resistance is measured in Ohms. Resistive loss can also be measured from using Current and Resistance, the equation looks like;
    $P={I^{2}\cdot R}\,$
Where P is power measured in watts.
# Introduction to political science
## Learning Objectives
#### Unit 1: The Bases Of Politics

* What is politics? Explain in detail.
* What is a nation-state? Define its elements.
* Discuss the contributions of many different political theorists.
* Compare and describe the different social contract theories.
* What is Democracy and a Republic?
* Compare and contrast authoritarianism and totalitarianism. Give examples of each.
* Using examples in Kenya define politics.
* What is military politics?

#### Unit 2: Political Thought

* Define the term ideology.
* Classic Liberalism vs. Modern Liberalism
* Outline the main tenets of Socialism, Communism, Fascism, Anarchism, etc.
* Culture vs. Politics
* Discuss the contributions of Feminism

#### Unit 3: Politics in History

* Identify world altering political events.
* Actors vs. Ideas
* Identify the different civilizations that attempted world conquest. Why?
* Discuss the American Revolution
* Discuss the Russian Bolshevik Revolution
* Discuss both World War I and II

#### Unit 4: Modern Politics

* Discuss the governing bodies of modern nation-states.
* What is the United Nations?
* Globalization, the savior or destroyer?
* Terrorism and its effect on politics.
* Can there really be Democracy in Iraq?
* The effect of economics in world politics.
* What is Capitalism?

## Class Procedures

This class will be instructed through reading materials, discussion and formal lecture. Please be aware that this class will require that you attend periodic live online voice lectures. After these lectures, students will be allowed to vocally debate and ask questions. These lectures will be once a week, and instructions on how and when to attend these lectures will be emailed to you upon enrollment.

#### EXAMS

There will be 4 writing component projects that will be considered exams through out the semester. This will require students to critically think about the various elements of their unit of study.
Final Exam will be comprehensive and consist of Multiple Choice, True/False and Matching.

#### Grade Computation

Lecture exams = 80% Final exam = 20%
Grade scale: 90-100 = A; 80-89 = B; 70-79 = C; 60-69 = D; below 60 = F

#### Attendance

Students are required to attend the once a week live online lecture. Most of the information needed to fulfill the exams will be discussed in these lectures. Students will be allowed to miss 1 lecture session, thereafter the student will be dropped from this class. The professor of this course gives the effort to teach for free, students must give the effort to attend.

## Students

If you have enrolled, please put you name below:

### users from Wikibooks

* Naroz Ali Awan
Konulu
* Zachjones4
* Cshelton
* alexbaldwin
* alaou
* madka
* Commandersa 14:48, 31 March 2006 (UTC)
* Wutasumi
* Ikron21
* Mirwan24
harpreet singh
* Jacky Jackson

## Related Reading from Wikipedia

* Political Science
* Comparative Politics
* Political Philosophy
# Introduction to physics (MIT)

Part of the School: Physics

### Mathematical background

The key mathematical concepts needed for introduction to physics includes basic calculus and linear algebra.

### Applications

Basic physics is required not only for more advanced work in physics, but also work in engineering.

### Resources

[MIT Physics I] [MIT Physics I]
# Introduction to nutrition
## The Food Pyramid

The food pyramid gives a great perspective on how to eat healthily. Have at least 3 ounces of grains each day, vary your veggies, don't go for the fruit juices, make sure your dairys are low-fat or fat-free and go for baked, broiled or grilled lean meat or poultry.

## How To Lay Off The Sweets

Everyone loves chocolate and candy, but they want to stay healthy, too. There are simple ways to avoid your sweets.
* Instead of reaching for jellybeans, reach for a sweet fruit! Strawberries, cherries, grapes, bananas and apples are great alternatives.
* If you want to eat healthy but have a little sweets at the same time, try dipping the tip of a strawberry into some melted chocolate. Or, you could do the same with a cherry.

## Healthy Breakfast Examples

Here are some examples of a healthy breakfast:
* eggs, whole grain cereal and milk, banana (could be replaced with oter fruit), orange juice (only half-3/4 of a cup full).
* fruit salad, croissant, milk
* oatmeal, milk, fruit

## Healthy Lunch and Dinner Examples

* turkey sandwich on wheat bread, carrots and celery
* green beans, mashed potatoes, pasta
* pizza, carrots, spinach

## Things to Avoid

These are some things that you should avoid:
* candy
* fruit juices
* oils and fats (potato chips, French fries, etc.)
* doughnuts, pastries, cakes etc.
# Introduction to probability and statistics

Welcome to the Basic Probability and Statistics learning project of the Wikiversity Master of Business Administration Program.

## Getting started

The grounding for many further concepts in business, as in other applied disciplines, is a thorough understanding of statistics. A good free source for understanding probability is Introduction to Probability. In particular regression analysis is going to be useful. Regression is fundamental to the concept of Beta in Finance and conjoint analysis in Marketing. In addition, the statistical concepts of standard deviation and variance are the fundamental concepts which underly the principle of pooling risk in operations management.
The directions on how to perform a regression analysis in Excel can be found online at Regression Analysis Using Microsoft Excel. Once you have completed a few regressions in Excel, you have performed the highest level of statistical analysis that most MBA's become familiar with. Congratulations! You are ready to move on.