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1 | 0 | machine learning | machine learning is the science of getting computers to act without being explicitly programmed self driving cars, speech recognition, and web search | trains computers to accurately recognize patterns in data for purposes of data analysis, prediction, and/or action selection by autonomous agents |
1 | 0 | machine learning | techniques allowing computers to 'improve performance' in certain tasks by making use of data (rather than being programmed explicitly for a task) | uses statistical techniques to give computers the ability to &"learn&" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed |
0 | 0 | machine learning | artificial intelligence in which computers continually teach themselves to make better decisions based on previous results and new data | trains computers to accurately recognize patterns in data for purposes of data analysis, prediction, and/or action selection by autonomous agents |
1 | 0 | machine learning | algorithms that are good at predicting. (based on knowledge, things we already know) | study of algorithms that computers use to perform certain tasks, helps decision making |
3 | 1 | machine learning | - the extraction of knowledge from data based on algorithms created from training data - focused on predicting outcomes based on previously unknown data | the extraction of knowledge from data based on algorithms created from training data technique for making a computer produce better results by learning from past experiences. |
1 | 0 | machine learning | a type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn. | a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. |
2 | 1 | machine learning | is about making machines get better at some task by learning from data, instead of having code rules. | is about building systems that can learn from data. learning means getting better at some task, given some performance measure. |
1 | 0 | machine learning | algorithms that can learn from data, or, computer programs that essentially program themselves by looking at information | type of ai broadly defined as software with the ability to learn or improve without being explicitly programmed |
2 | 1 | machine learning | machine learning is a field of computer science that gives computer systems the ability to &"learn&" with data, without being explicitly programmed. | in the 1950s the term &" machine learning&" was coined to refer to programs that gave computers the ability to learn from data. |
0 | 0 | machine learning | technique for making a computer produce better results by gathering data and learning from past experiences. | a field of study interested in the development of computer algorithms to transform data into intelligent action ex. facebook auto friend tagging, uber estimated time arrival |
1 | 0 | machine learning | the use of data-driven algorithms that perform better as they have more data to work with; generally uses cross-validation | the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the word |
1 | 0 | machine learning | a field of study interested in the development of computer algorithms to transform data into intelligent action ex. facebook auto friend tagging, uber estimated time arrival | artificial intelligence in which computers continually teach themselves to make better decisions based on previous results and new data |
3 | 1 | reverse engineering | the process of analyzing a system to identify components and their interrelations and create representations of the system in another form or at a higher lever of abstraction | it is the process of analyzing a subject system to identify the system components and their relationship and create a representation of a system in another form |
3 | 1 | reverse engineering | the process of analyzing a system to identify components and their interrelations and create representations of the system in another form or at a higher lever of abstraction | the process of analyzing an existing software system and creating a new version of the system at a higher level of abstraction |
1 | 0 | reverse engineering | where a program is decoded to extract information from it; it helps with documenting the organization and functionality of a system | analyze the program to understand it, information extraction |
1 | 0 | reverse engineering | involves taking apart a competitor's product, analyzing it, and creating an improved product that does not infringe on the competitor's patents, if any exist | designing products based on existing designs thru measurement and deconstruction |
0 | 0 | reverse engineering | the process of analyzing an existing software system and creating a new version of the system at a higher level of abstraction | process of analyzing a system and understand its structure and functionality |
1 | 0 | reverse engineering | the process of analysing an existing system to identify its components and their interrelationships, to allow the creation of a similar system | process of analyzing a system and understand its structure and functionality |
2 | 1 | reverse engineering | behavior to source code to design to requirements | recover requirements or design info from source code |
1 | 0 | reverse engineering | the process of disassembling a product to analyze its design features. | the process of duplicating/analyzing an existing component, subassembly, or product. |
2 | 1 | reverse engineering | > leads to a new understanding about products > process of analyzing the products function and features > begins with a product and ends with an understanding | the process of taking apart an object to see how it works in order to duplicate the object. it is legal to acquire a trade secret through reverse engineering. |
3 | 1 | reverse engineering | the process of taking something apart and analyzing its workings in detail with the intention of understanding its structure function and operation | the process of taking something apart and analyzing its workings in detail, usually with the intention of understanding its function. |
1 | 0 | reverse engineering | the process of analyzing a system to identify components and their interrelations and create representations of the system in another form or at a higher lever of abstraction | process of analyzing a system and understand its structure and functionality |
0 | 0 | reverse engineering | where a program is decoded to extract information from it; it helps with documenting the organization and functionality of a system | the process of analysing to identify its components and their interrelationships, to allow the creation of a similar system. |
1 | 0 | reverse engineering | original source code is recreated from examaning outputs of software. focuses on recreating product than copying code. | analysing a product and its parts to understand how it works to recreate the original design |
3 | 1 | reverse engineering | the process of analysing an existing system to identify its components and their interrelationships, to allow the creation of a similar system | it is the process of analyzing a subject system to identify the system components and their relationship and create a representation of a system in another form |
0 | 0 | reverse engineering | automated tools that read program source code as input and create graphical and textual representations of design-level information such as program control structures, data structures, logical flow, and data flow. | the process of analysing to identify its components and their interrelationships, to allow the creation of a similar system. |
2 | 1 | reverse engineering | the process of analysing to identify its components and their interrelationships, to allow the creation of a similar system. | the process of extracting knowledge or design information from anything man-made and reproducing it or reproducing anything based on the extracted information. |
2 | 1 | reverse engineering | a strategy used to find answers to questions about an existing product that are later used in the design of another project. | examine the construction or composition of another manufacturer's product in order to create (a duplicate or similar product). |
0 | 0 | reverse engineering | where a program is decoded to extract information from it; it helps with documenting the organization and functionality of a system | the process of extracting knowledge or design information from anything man-made and reproducing it or reproducing anything based on the extracted information. |
1 | 0 | reverse engineering | analyze the program to understand it, information extraction | the process of extracting knowledge or design information from anything man-made and reproducing it or reproducing anything based on the extracted information. |
1 | 0 | reverse engineering | the process of analysing to identify its components and their interrelationships, to allow the creation of a similar system. | analyze the program to understand it, information extraction |
2 | 1 | reverse engineering | the process of discovering the technological principles of a device, object or system through analysis of its structure, function, and operation. | the process of learning about the device / object from the inside out. |
1 | 0 | reverse engineering | the process of analysing an existing system to identify its components and their interrelationships, to allow the creation of a similar system | the process of analyzing an existing software system and creating a new version of the system at a higher level of abstraction |
0 | 0 | classification rules | results are often expressed in the form of rules | they predict the classification of given attribute (in terms of whether to play or not) |
0 | 0 | service providers | organizations with computers connected to the internet that are willing to provide access to software, data and storage | - regional authorities - counties - special districts - cities - schools -conservancies and friends groups financed primarily by taxes with user fees as a supplement source of income |
0 | 0 | service providers | any person providing an iss could be for free - 'normally' remuneration. | organizations with computers connected to the internet that are willing to provide access to software, data and storage |
2 | 1 | mobile applications | an app designed to run on mobile devices | different edition of software that is designed specifically for mobile use |
1 | 0 | mobile applications | (type of application software) small programs primarily designed for mobile devices (e.g., smartphones and tablets) | are add-on programs for a variety of mobile devices including smartphones and tablets |
0 | 0 | mobile applications | an app designed to run on mobile devices | add on programs for mobile or smart phones, app store provides access to apps |
2 | 1 | mobile applications | are add-on programs for a variety of mobile devices including smartphones and tablets | different edition of software that is designed specifically for mobile use |
1 | 0 | mobile applications | software programs that run on mobile devices and give users access to certain content | different edition of software that is designed specifically for mobile use |
2 | 1 | mobile applications | (type of application software) small programs primarily designed for mobile devices (e.g., smartphones and tablets) | add on programs for mobile or smart phones, app store provides access to apps |
0 | 0 | mobile applications | applications designed to run on mobile devices. these can be used for creating documents, taking pictures, listening to music, playing games or finding directions. | refers to programs that are designed to help users complete a specific activity or task |
1 | 0 | mobile applications | add on programs for mobile or smart phones, app store provides access to apps | different edition of software that is designed specifically for mobile use |
2 | 1 | mobile applications | (type of application software) small programs primarily designed for mobile devices (e.g., smartphones and tablets) | different edition of software that is designed specifically for mobile use |
2 | 1 | mobile applications | an app designed to run on mobile devices | (type of application software) small programs primarily designed for mobile devices (e.g., smartphones and tablets) |
2 | 1 | mobile applications | an app designed to run on mobile devices | software programs that run on mobile devices and give users access to certain content |
3 | 1 | mobile applications | an app designed to run on mobile devices | are add-on programs for a variety of mobile devices including smartphones and tablets |
3 | 1 | mobile applications | add on programs for mobile or smart phones, app store provides access to apps | are add-on programs for a variety of mobile devices including smartphones and tablets |
0 | 0 | mobile applications | software programs that run on mobile devices and give users access to certain content | are add-on programs for a variety of mobile devices including smartphones and tablets |
1 | 0 | mobile applications | software programs that run on mobile devices and give users access to certain content | add on programs for mobile or smart phones, app store provides access to apps |
1 | 0 | association rule | likelihood of buying another product with a certain product what people buy together descriptive if <antecedent> then <consequent> | • when you connect one thing to another product • ex. beer + diapers = happiness |
1 | 0 | association rule | an implication expression of the form x --> y, where x and y are itemsets ex: {milk, diaper} --> {beer} do not mean causality... more like co-occurrence | describes relationship between two itemsets. x --> y - x is antecedent (lhs) - y is consequent (rhs) |
1 | 0 | association rule | an implication expression of the form x -> y, where x and y are itemsets ex. {milk, diaper} -> {beer} | describes relationship between two itemsets. x --> y - x is antecedent (lhs) - y is consequent (rhs) |
0 | 0 | association rule | used to discover interesting relations between attributes in large datasets. | discover item sets that frequently occur together |
0 | 0 | physical resources | manufacturing facilities, buildings, vehicles, machines, systems, distribution networks | personnel material machines money |
3 | 1 | cluster analysis | identify groups of entities with similar characteristics (find groups of similar customers from customer order and demographic data) | statistical techniques identify groups of entities that have similar characteristics. common use - fidnd groups of similar customers from orders and demographic data |
3 | 1 | cluster analysis | statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. unsupervised data mining technique | common unsupervised technique -statistical techniques identify groups of entities that have similar characteristics -common use is to find groups of similar customers from customer order and demographic data |
1 | 0 | cluster analysis | class label is unknown: group data to form new classes, e.g., cluster houses to find distribution patterns | a collection of techniques that seek to group or segment a collection of objects into subsets or clusters. a data reduction technique and is primarily descriptive |
3 | 1 | cluster analysis | statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. unsupervised data mining technique | unsupervised data mining technique where statistics are used to identify similar groups of people. like how to target a particular group of customers that have placed similar past orders |
3 | 1 | cluster analysis | common unsupervised data mining technique that includes using statistical techniques to identify groups of entities that have similar characteristics | analytic unsupervised data mining technique that identifies groups of entities that have similar characteristics |
0 | 0 | cluster analysis | using statistical methods, a computer program explores data to find groups with common and previously unknown characteristics | a model that determines previously unknown groupings of data |
3 | 1 | cluster analysis | common unsupervised data mining technique that includes using statistical techniques to identify groups of entities that have similar characteristics | unsupervised statistical techniques identify group of entities that have simar characteristics |
3 | 1 | cluster analysis | statistical techniques identify groups of entities that have similar characteristics. common use - fidnd groups of similar customers from orders and demographic data | common unsupervised technique -statistical techniques identify groups of entities that have similar characteristics -common use is to find groups of similar customers from customer order and demographic data |
0 | 0 | cluster analysis | identify groups of entities with similar characteristics (find groups of similar customers from customer order and demographic data) | unsupervised data mining technique where statistics are used to identify similar groups of people. like how to target a particular group of customers that have placed similar past orders |
1 | 0 | cluster analysis | class label is unknown: group data to form new classes, e.g., cluster houses to find distribution patterns | collection of techniques that seek to group of segment a collection of objects into subsets of clusters |
3 | 1 | cluster analysis | identifying groups in the data that have similar characteristics and patterns unsupervised dm | -common unsupervised technique -groups entities based on similar characteristics -findings obtained solely by data analysis |
2 | 1 | cluster analysis | arranging items or values based on different variables into &"natural&" groups | the process of arranging terms or values based on different variable into &"natural&" groups. a forecasting technique that employs a series of past data points to make a forecast |
3 | 1 | cluster analysis | goal - divide n observations into clusters so that elements within a cluster look very similar while those in different clusters look diverse | to find grps of closely related observations so that observations that belong to the same cluster are more similar to each other than observations that belong to other clusters |
3 | 1 | cluster analysis | identifying groups in the data that have similar characteristics and patterns unsupervised dm | an unsupervised technique that uses statistical techniques to identify groups of entities that have similar characteristics |
1 | 0 | cluster analysis | arranging items or values based on different variables into &"natural&" groups | the process of arranging terms or values based on different variables into &"natural&" groups. used for understanding the makeup of an industry's different areas. |
3 | 1 | cluster analysis | analytic unsupervised data mining technique that identifies groups of entities that have similar characteristics | unsupervised statistical techniques identify group of entities that have simar characteristics |
3 | 1 | cluster analysis | unsupervised data mining technique where statistics are used to identify similar groups of people. like how to target a particular group of customers that have placed similar past orders | common unsupervised technique -statistical techniques identify groups of entities that have similar characteristics -common use is to find groups of similar customers from customer order and demographic data |
3 | 1 | cluster analysis | statistical techniques identify groups of entities that have similar characteristics -common use for cluster analysis is to find groups of similar customers from customer order and demographic data | common unsupervised technique -statistical techniques identify groups of entities that have similar characteristics -common use is to find groups of similar customers from customer order and demographic data |
2 | 1 | cluster analysis | statistical techniques identify groups of entities that have similar characteristics -common use for cluster analysis is to find groups of similar customers from customer order and demographic data | statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. unsupervised data mining technique |
3 | 1 | cluster analysis | statistical techniques identify groups of entities that have similar characteristics -common use for cluster analysis is to find groups of similar customers from customer order and demographic data | statistical techniques identify groups of entities that have similar characteristics. common use - fidnd groups of similar customers from orders and demographic data |
2 | 1 | cluster analysis | statistical techniques identify groups of entities that have similar characteristics -common use for cluster analysis is to find groups of similar customers from customer order and demographic data | unsupervised data mining technique where statistics are used to identify similar groups of people. like how to target a particular group of customers that have placed similar past orders |
3 | 1 | cluster analysis | an unsupervised technique that uses statistical techniques to identify groups of entities that have similar characteristics | -common unsupervised technique -groups entities based on similar characteristics -findings obtained solely by data analysis |
3 | 1 | cluster analysis | statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. unsupervised data mining technique | statistical techniques identify groups of entities that have similar characteristics. common use - fidnd groups of similar customers from orders and demographic data |
1 | 0 | cluster analysis | arranging items or values based on different variables into &"natural&" groups | the process of arranging terms or values based on different variables into &"natural&" groups. used for understanding the makeup of an industry's different areas. also known as segmentation. |
1 | 0 | cluster analysis | a collection of techniques that seek to group or segment a collection of objects into subsets or clusters. a data reduction technique and is primarily descriptive | divides data into groups that are meaningful/useful. objects in a cluster share the same characteristics. |
2 | 1 | cluster analysis | unsupervised data mining technique where statistics are used to identify similar groups of people. like how to target a particular group of customers that have placed similar past orders | statistical techniques identify groups of entities that have similar characteristics. common use - fidnd groups of similar customers from orders and demographic data |
0 | 0 | cluster analysis | statistical technique to identify groups of entities with similar characteristics; used to find groups of similar customers from customer order and demographic data. unsupervised data mining technique | identify groups of entities with similar characteristics (find groups of similar customers from customer order and demographic data) |
1 | 0 | cluster analysis | identify groups of entities with similar characteristics (find groups of similar customers from customer order and demographic data) | common unsupervised technique -statistical techniques identify groups of entities that have similar characteristics -common use is to find groups of similar customers from customer order and demographic data |
3 | 1 | space complexity | how much space the algorithm takes | the amount of memory an algorithm or data structure needs |
1 | 0 | space complexity | amount of computer memory required during program execution as a function of input size | what amount of extra space is required for module to execute |
1 | 0 | space complexity | the space needed by an algorithm expressed as a function of the input size. | what amount of extra space is required for module to execute |
2 | 1 | space complexity | maximum number of nodes in memory | maximum number of nodes stored in memory -expressed in terms of b, d, m |
2 | 1 | space complexity | time is not the only thing that matters in an algorithm. we might also care about the amount of memory or space-required by an algorithm. | how much memory is being used in general |
3 | 1 | space complexity | amount of computer memory required during program execution as a function of input size | the space needed by an algorithm expressed as a function of the input size. |
2 | 1 | space complexity | the amount of memory needed by a program to run to completion | how much memory is being used in general |
1 | 0 | space complexity | how much space (inside ram) is required | amount of space used |
1 | 0 | space complexity | time is not the only thing that matters in an algorithm. we might also care about the amount of memory or space-required by an algorithm. | the amount of memory needed by a program to run to completion |
0 | 0 | service quality | service quality dimensions are reliability, assurance, tangibles, empathy, and responsiveness | timeliness, turnaround time, accuracy, thoroughness, accessibility, convenience, courtesy, and safety - often process (measurable) indicators measuring compliance with established standards. |
2 | 1 | service quality | the experiences and perceptions of patients and other stakeholders. | customers' perceptions of how well a service meets or exceeds their expectations |
2 | 1 | protocol stack | layering different protocols on top of one another | or a protocol suite, is made up of multiple protocols used to exchange information between computers |
2 | 1 | protocol stack | tcp/icp 1. physical 2. data link 3. network 4. transport 5. application | the collection of networking protocols that operate at the various layers |
1 | 0 | protocol stack | networks use more than one protocol, and the collection of protocols for a network is referred to as a protocol stack. | al known as a protocol suite and is multiple protocols that work together to provide a network service or application. |
1 | 0 | protocol stack | different layers and are stacked one of another the set of software used to understand the different protocols | the set of software required to process a set of protocols at various layers |
Subsets and Splits