Big Data & Data Science at FOM Hochschule Für Oekonomie & Management | Flashcards & Summaries

Big Data & Data Science at FOM Hochschule für Oekonomie & Management

Flashcards and summaries for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management

Arrow Arrow

It’s completely free

studysmarter schule studium
d

4.5 /5

studysmarter schule studium
d

4.8 /5

studysmarter schule studium
d

4.5 /5

studysmarter schule studium
d

4.8 /5

Study with flashcards and summaries for the course Big Data & Data Science at the FOM Hochschule für Oekonomie & Management

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

Common Variable Types

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What is a qualitative variable?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What measurement scales are correct?
This was only a preview of our StudySmarter flashcards.
Flascard Icon Flascard Icon

Millions of flashcards created by students

Flascard Icon Flascard Icon

Create your own flashcards as quick as possible

Flascard Icon Flascard Icon

Learning-Assistant with spaced repetition algorithm

Sign up for free!

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What expresses the nominal scale?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What expresses the ordinal scale?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

Definition of Experience E?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What is a Task and what is the character?
This was only a preview of our StudySmarter flashcards.
Flascard Icon Flascard Icon

Millions of flashcards created by students

Flascard Icon Flascard Icon

Create your own flashcards as quick as possible

Flascard Icon Flascard Icon

Learning-Assistant with spaced repetition algorithm

Sign up for free!

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

How does the Loss Function behave if the predictions deviate too much from the actual results?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What expresses the metric scale?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

What are the main key facts of reinforcement learning?

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

Choose the regression algorithm!
This was only a preview of our StudySmarter flashcards.
Flascard Icon Flascard Icon

Millions of flashcards created by students

Flascard Icon Flascard Icon

Create your own flashcards as quick as possible

Flascard Icon Flascard Icon

Learning-Assistant with spaced repetition algorithm

Sign up for free!

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

To what refers Iterations?

Your peers in the course Big Data & Data Science at the FOM Hochschule für Oekonomie & Management create and share summaries, flashcards, study plans and other learning materials with the intelligent StudySmarter learning app.

Get started now!

Flashcard Flashcard

Exemplary flashcards for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management on StudySmarter:

Big Data & Data Science

Common Variable Types
Qualitative Variable

Big Data & Data Science

What is a qualitative variable?
Also called categorical variables, take on values that are names or labels e.g. the gender

Big Data & Data Science

What measurement scales are correct?
Nominal scale

Big Data & Data Science

What expresses the nominal scale?
Characteristic attributes can be distinguished, eg gender. A subtype of it with only two categories (eg male/female) is called dichotomous

Big Data & Data Science

What expresses the ordinal scale?
Characteristic attributes can be distinguished and ranked. Eg educational achivement.

! Intervals between the values can neither be compared nor interpreted

Big Data & Data Science

Definition of Experience E?
  • Is defined as a set of training instances from a dataset that is used by a computer program in order to learn how to execute a task T
  • eg Experience is obtained by the computer program by playing checkers games against itself

Big Data & Data Science

What is a Task and what is the character?
  • Defined as a job a computer program has to learn in order to execute it
  • Learning itself is not considered as a discrete task
  • eg Teaching a computer in how to play checkers, then playing checkers itself is the Task T

Big Data & Data Science

How does the Loss Function behave if the predictions deviate too much from the actual results?
If for a given set of parameters the predictions deviate too much from the actual results, the loss function will output a higher number compared to predictions that are good

Big Data & Data Science

What expresses the metric scale?
  • Characteristic attributes can be distinguished and ranked
  • Intervals can be compared
  • Metric scale divides further into interval and ratio scale
  • Ratio Scale has a naturally given point of origin (eg body weight)
  • Interval scale has an artificially given point of origin (eg calculation times)




Big Data & Data Science

What are the main key facts of reinforcement learning?
  • Algorithms from the group of reinforcement learning produce agents rather than classical models that receive information from the environment and react to it by performing an action
  • information that the agent receives from the environment in form of numerical data is called state which is stored and then used for choosing the right action
  • The result of the action, the agent receives a reward that can be either positive or negative which is then used as a feedback to the agent in order to update its parameters and change its future actions
  • process of learning and training is a process of trial and error 
    • agent finds itself in various states and gets punished every time it takes the wrong action and thus starts learning how to take better actions

Big Data & Data Science

Choose the regression algorithm!
linear regression

Big Data & Data Science

To what refers Iterations?
The number of batches need to complete one epoch

For a training set with 1000 instances and a batch size of 250 it would take 4 iterations to complete 1 epoch

Sign up for free to see all flashcards and summaries for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management

Singup Image Singup Image
Wave

Other courses from your degree program

For your degree program Big Data & Data Science at the FOM Hochschule für Oekonomie & Management there are already many courses on StudySmarter, waiting for you to join them. Get access to flashcards, summaries, and much more.

Back to FOM Hochschule für Oekonomie & Management overview page

Betriebssysteme

Human Ressources

Datenbanken relevant

OOP chillig

Are you with me?

Big Data

Netzwerke

3. Semester WI - BIS

IT-Management

Software Engineering

IT Infrastruktur

Letztendlich Forschung

Wirtschaftsinformatik Basics Neu

Data Science at

IUBH Internationale Hochschule

Big Data / Data Science at

FOM Hochschule für Oekonomie & Management

Big Data & Big Data Science at

FOM Hochschule für Oekonomie & Management

Big Data & Data Science 2021 at

FOM Hochschule für Oekonomie & Management

Data Science & BI at

International School of Management

Similar courses from other universities

Check out courses similar to Big Data & Data Science at other universities

Back to FOM Hochschule für Oekonomie & Management overview page

What is StudySmarter?

What is StudySmarter?

StudySmarter is an intelligent learning tool for students. With StudySmarter you can easily and efficiently create flashcards, summaries, mind maps, study plans and more. Create your own flashcards e.g. for Big Data & Data Science at the FOM Hochschule für Oekonomie & Management or access thousands of learning materials created by your fellow students. Whether at your own university or at other universities. Hundreds of thousands of students use StudySmarter to efficiently prepare for their exams. Available on the Web, Android & iOS. It’s completely free.

Awards

Best EdTech Startup in Europe

Awards
Awards

EUROPEAN YOUTH AWARD IN SMART LEARNING

Awards
Awards

BEST EDTECH STARTUP IN GERMANY

Awards
Awards

Best EdTech Startup in Europe

Awards
Awards

EUROPEAN YOUTH AWARD IN SMART LEARNING

Awards
Awards

BEST EDTECH STARTUP IN GERMANY

Awards