277 Data Science Key Terms, Explained

277 Data Science Key Terms, Explained

This publication presents a collection of key terms related to data science with concise and harmless definitions, organized into 12 distinct topics. Beginning with Big Data and progressing in natural language processing, this definition train stops at learning machines, databases, Apache Hadoop, and many others. This may take time, but once you have completed the terminology presented here, you should have a good idea of ​​the key terms of importance in data science. And do not worry if the settings are too thin for you; Links abound to extend related reading opportunities where appropriate.

20 key terms of the data, explained

Important information, if in a way you did this on this site and you did not hear that term as it grew to become a popular term for at least ten and a half years, I really do not know what to say.

But simply because we hear the term, or participate (or the opposite) of its flawless use that does not really mean that we know what it really means, or what it encompasses completely. In fact, trying to exhaustively describe what Big Data is in an article would be absurd, not the least of the reasons why there is not an exhaustive description agreed upon, nor should it be. Collecting some important terms associated with large data is not a bad idea, however, since it is based on a common basis to be able to move forward.

12 Key Terms of Machine Learning, Explained

This is the first in a series of articles on KDnuggets that will offer concise explanations of a set of related terms (machine learning in this case), specifically taking a perfect approach for those seeking to isolate and define. After some reflection, it was determined that these types of fundamental and informative publications have not been sufficiently exposed in the past.

So let's start with an overview of machine learning and related topics.

10 Clustering Key Terms, Explained

Grouping is a method of data analysis that aggregates data points together to "maximize intraclass similarity and minimize class similarity" (Han, Kamber & Pei) without using predefined point tags. An unsupervised learning technique). This publication introduces keywords for common techniques in cluster analysis.

14 key terms of learning, explained

In-depth learning is a relatively new term, although it existed before the dramatic change in late online searches. Due to the boom in research and industry, mainly due to its incredible success in several different areas, in-depth learning is the process of applying deep neural network technologies, i.e. multi-layered neural network architectures to solve problems. Full learning is a process, such as data mining, that uses deep neural network architectures, which are specific types of machine learning algorithms.

16 Key Terms in the Database, Explained

Data must be organized, provided and served. It must be stored and processed so that it can be transformed into information and then perfected in knowledge. The data storage mechanism, which facilitates these transformations, is clearly the database.

This publication presents 16 key database concepts and their corresponding concise and direct definitions.

15 Descriptive statistics Main conditions, explained

Statistics, although a core set of data science tools, are often neglected in favor of stronger technical skills such as programming. Even machine learning algorithms, with their dependence on mathematical concepts such as algebra and computation - much less the statistics! - are often treated at a higher level than necessary to appreciate the underlying mathematics, perhaps leading to "data searchers" who do not have a fundamental understanding of one of the major aspects of their profession.

11 key terms of introduction to predictive analytics, explained

This article compiles the key definitions included in PAW's popular, award-winning Predictive Analytics book The Power to predict who will click, buy, lie, or die (revised and updated, 2016) as a textbook at more than 35 universities, but reads like pop science, dubbed "The Freakonomics of Big Data."

20 Key Terms of Cloud Computing, Explained

Cloud computing primarily enables organizations to get their deployed applications faster without requiring excessive maintenance, which is managed by the service provider. This also leads to better use of IT resources depending on the needs and requirements of a company from time to time.

While the Internet is full of cloud-related terms, here are some pretty basic but important elements that one should certainly know about. Knowing these key terms will help you understand industry developments and future trends in cloud computing.

16 Major Hadoop Terms Explained

Hadoop is a very powerful open source platform run by the Apache Foundation. The Hadoop platform is based on Java technologies and able to handle a huge volume of heterogeneous data in a clustered environment. Its scalability is perfect for distributed computing.

The Hadoop ecosystem consists of major components of Hadoop and other associated tools. In the main components, the Hadoop Distributed File System (HDFS) and the MapReduce programming model are the two most important concepts. Among the associated tools, Hive for SQL, Pig for data flow, Zookeeper for service management, etc. are important. Let's explain these terms in detail.

13 key terms of Apache Spark, explained

One of the reasons why Apache Spark has become so popular is because Spark provides data engineers and data scientists with a powerful and unified engine that is fast (100 times faster than Apache Hadoop for large-scale data processing) and data Science easy to use. This enables data professionals to solve their interactive and scalable machine learning, graphics, dissemination and interactive process real-time processing problems.

In this blog post, we'll discuss some of the key terms encountered while working with Apache Spark.

12 Internet of the main things explained

Internet of Things (IoT) is the concept for conducting Internet-based communications between physical objects, sensors and controllers. This publication will definitely define 12 key terms for the Internet of Things.

18 Key Terms of Natural Language Processing, Explained

This publication aims to serve as an introductory paper, adopting an unsolicited approach to defining a key NLP terminology. Although you are certainly not a linguist expert after reading this, we hope you can better understand some NLP speeches and learn how to learn more about topics.

So, that is, 18 terms of natural language processing, defined concisely, with links to other readings where appropriate.