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short research paper?
WAN Technologies Paper: Research Point-to-Point (dedicated), Packet Switched, and Circuit Switched WAN protocols/circuits/ ...
short research paper?
WAN Technologies Paper: Research Point-to-Point (dedicated), Packet Switched, and Circuit Switched WAN protocols/circuits/types. Define each protocol and describe at least two data transmission technologies associated with the protocol. Include the bandwidth limitations of each technology and protocol.Support your information and make sure all information sources are appropriately cited.The paper must use APA 6th ed., 7th printing formatting and contain a title page, 3 to 5 pages of content, and a minimum of fivepeer-reviewed references..Assignment Information Resource(s):Network Protocols Handbook - Javvin Technologies, Inc. Network Protocols Handbookplease read and write it accordinglyApa and no plagiarism
Campbellsville University Forensic Design Assessments Discussion
This task relates to a sequence of assessments that will be repeated across Chapters 6, 7, 8, 9 and 10. Select any example ...
Campbellsville University Forensic Design Assessments Discussion
This task relates to a sequence of assessments that will be repeated across Chapters 6, 7, 8, 9 and 10. Select any example of a visualisation or infographic, maybe your own work or that of others. The task is to undertake a deep, detailed ‘forensic’ like assessment of the design choices made across each of the five layers of the chosen visualisation’s anatomy. In each case your assessment is only concerned with one design layer at a time. For this task, take a close look at the interactivity choices: Start by identifying all the interactive features deployed, listing them under the headers of either data or presentation adjustments How suitable are the choices and deployment of these interactive features? If they are not, what do you think they should have been? Go through the set of ‘Influencing factors’ from the latter section of the book’s chapter to help shape your assessment and to possibly inform how you might tackle this design layer differently Also, considering the range of potential interactive features and functions, what would you do differently or additionally? Assignment Link: http://book.visualisingdata.com/chapter/chapter-7 Assignment Length (word count): At least 550 words (not including direct quotes). References: At least three peer-reviewed, scholarly journal references.
CIS 510 Strayer University Project Risk and Feasibility Essay
Considering that enterprise system implementations fail 40 percent of the time, there is substantial risk involved—risk ...
CIS 510 Strayer University Project Risk and Feasibility Essay
Considering that enterprise system implementations fail 40 percent of the time, there is substantial risk involved—risk that, in many cases, can put a company out of business.Research project risk and feasibility. For each of the following risk categories, discuss:What the type of risk is.Ways to help mitigate the risk category.Examine your current place of work, or an organization of your choice, and write a paper in which you discuss:Organizational Risks.Technical Risks.Resource Risks.Schedule Risks.Use at least three quality resources. Note: Wikipedia and similar websites do not qualify as quality resources.This course requires the use of Strayer Writing Standards. For assistance and information, please refer to the Strayer Writing Standards link in the left-hand menu of your course.The specific course learning outcome associated with this assignment is:Assess the risks and mitigation strategies that are common to enterprise system implementations.
Information Gathering or Data Collection Discussion and Responses
Textbook :( I DONT HAVE THE TEXTBOOK)
Sharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial ...
Information Gathering or Data Collection Discussion and Responses
Textbook :( I DONT HAVE THE TEXTBOOK)
Sharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support 11E. ISBN: 978-0-13-519201-6
Create a discussion thread (with your name) and answer the following question:
Discussion (Chapter 6): List and briefly describe the nine-step process in con-ducting a neural network project.
Post
hey can you give replies to these 2 posts of my peers , as its part of the question. thanks1) Like any other project, conducting an artificial neural network requires preparing the data and the tools necessary to efficiently and accurately produce a desired product. According to Sharda et al (2020),the first step in the process of conducting an ANN project is gathering the data needed, arranging data to make sure that it is suitable for the ANN, and mold it into usable formats. The second step involves grouping data in the right clusters or training sets and validating the data(Sharda et al.,2020). Once the suitable data is ready, the next step is deciding on which network architecture will be used, and an appropriate learning algorithm is selected (Sharda et al.,2020). According to Sharda et al (2020) the fifth step involves customizing or tuning the parameters for the intended network and initializing the weights. Each neural network requires a specific data application, therefore, Sharda et al(2020) pointed out that the once the weights and the parameters are initialized, the next step is to transform the data into formats that are appropriate for the desired ANN.In step seven and eight, the input data and the desired output from the training sets are introduced to the ANN, and the neural network adjusts the weights in order to produce a desirable output (Sharda et al.,2020). After the weights have been adjusted, the created and tested neural network is deployed and used on new input data, in order to produce a different desired output and decision makers can decide if the right ANN was produced, and they would suggest modifications if deemed necessary (Sharda et al.,2020).ReferenceSharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support 11E. ISBN: 978-0-13-519201-62) Neural Network Project
Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than a replica of how the brain functions (Sharda et al., 2020).
Step 1: Collect, organize, and format the data: The data to be used for training and testing the networks are collected. Important considerations are that the particular problem is amenable to a neural network solution and that adequate data exist and can be obtained (Turban et al., 2014).
Step 2: Separate data into training, validation, and testing sets: The training data must be identified, and a plan must be made for testing the performance of the network.
Step 3: Decide on network architecture and design: A network architecture and design are selected. The availability of a particular development tool or the capabilities of the development personnel may determine the type of neural network to be constructed (Turban et al., 2014).
Step 4: Select a learning algorithm: A learning method is selected. Important considerations are the exact number of neutrons and the number of layers. Some packages use genetic algorithms to choose the network design (Turban et al., 2014).
Step 5: Set network parameters and initialize their values: It is followed by the modification of the parameters as training performance feedback is received.
Step 6: Initialize weights and start training: This may also require writing software to preprocess the data or performing these operations directly in an ANN package (Turban et al., 2014).
Step 7: Stop training, freeze the network weights: The network computes the outputs and adjusts the weights until the computed outputs are within an acceptable tolerance of the known outputs for the input cases (Turban et al., 2014).
Step 8: Test the trained network: It is conducted iteratively by presenting input and desired or known output data to the network.Step 9: Deploy the network for use on an unknown new case: Now, the network can produce the desired outputs.ReferencesSharda, R., Delen, D., & Turban, E. (2020). Analytics, Data Science, & Artificial Intelligencesystems for decision support, global edition. Place of publication not identified: PEARSON EDUCATION Limited.Turban, E., Sharda, R., & Delen, D. (2014). Decision support and business intelligence systems.Harlow, Essex: Pearson.1
5 pages
Harassment Stalking
1. The use of a password is one of the most common modes of security protection system around the world with 99% of all mo ...
Harassment Stalking
1. The use of a password is one of the most common modes of security protection system around the world with 99% of all mobile and computer ...
Explain KPIs as they relate to web analytics
Assignment Instructions:Explain KPIs what are they, as they apply to web analytics.Explain your position if you agree or d ...
Explain KPIs as they relate to web analytics
Assignment Instructions:Explain KPIs what are they, as they apply to web analytics.Explain your position if you agree or disagree with their relevance in web analytics.Explain your position.Class: You may find newer and older resources listed each week in the Lessons and Assignments; however, the older resources are still relevant in content and concept. The relevancy is noted in that they build on the structural foundation of web analytics. We must be aware that Web Analytics is always in motion, and organizations are seeking to create actionable insights driving the decision making process.Class, please feel free to explore your own research for eBooks, journals and articles that best answer the topics and assignments. Do your best to locate resources that are no more than three (3) years old. DO NOT USE WIKIPEDIA AS A RESOURCE AND OR REFERENCE.Unoriginal Content:Your essay may contain no more than 1% quotes from other sources. Paraphrase what you read instead of copying and pasting. You may not re-use work that you have submitted in previous classes. All work in this class must be original.Essays that contain more than 20% unoriginal content will not earn any credit. Essays that contain between 3% - 19% unoriginal content will receive a substantial point deduction. Paraphrase instead of copying and pasting. Please note there is a difference between unoriginal content and plagiarism. Unoriginal content is correctly quoted and cited. Plagiarized sentences and paragraphs are not correctly quoted or cited. Plagiarism will result in an automatic zero for this assignment.Helpful Assignment Articles Web Links and Readings:KPI Example PDF Report2014: Top 5 Google Analytics KPIs: A Beginner’s Guide to Web Analyticshttp://www.datapine.com/blog/top-5-google-analytics-kpis/2012: http://www.kaushik.net/avinash/measure-choose-smarter-kpis-incentives/2011: http://www.kaushik.net/avinash/best-web-metrics-kpis-small-medium-large-business/2010: http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/2009: http://www.kaushik.net/avinash/insights-web-analytics-kpi-measurement-techniques/
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short research paper?
WAN Technologies Paper: Research Point-to-Point (dedicated), Packet Switched, and Circuit Switched WAN protocols/circuits/ ...
short research paper?
WAN Technologies Paper: Research Point-to-Point (dedicated), Packet Switched, and Circuit Switched WAN protocols/circuits/types. Define each protocol and describe at least two data transmission technologies associated with the protocol. Include the bandwidth limitations of each technology and protocol.Support your information and make sure all information sources are appropriately cited.The paper must use APA 6th ed., 7th printing formatting and contain a title page, 3 to 5 pages of content, and a minimum of fivepeer-reviewed references..Assignment Information Resource(s):Network Protocols Handbook - Javvin Technologies, Inc. Network Protocols Handbookplease read and write it accordinglyApa and no plagiarism
Campbellsville University Forensic Design Assessments Discussion
This task relates to a sequence of assessments that will be repeated across Chapters 6, 7, 8, 9 and 10. Select any example ...
Campbellsville University Forensic Design Assessments Discussion
This task relates to a sequence of assessments that will be repeated across Chapters 6, 7, 8, 9 and 10. Select any example of a visualisation or infographic, maybe your own work or that of others. The task is to undertake a deep, detailed ‘forensic’ like assessment of the design choices made across each of the five layers of the chosen visualisation’s anatomy. In each case your assessment is only concerned with one design layer at a time. For this task, take a close look at the interactivity choices: Start by identifying all the interactive features deployed, listing them under the headers of either data or presentation adjustments How suitable are the choices and deployment of these interactive features? If they are not, what do you think they should have been? Go through the set of ‘Influencing factors’ from the latter section of the book’s chapter to help shape your assessment and to possibly inform how you might tackle this design layer differently Also, considering the range of potential interactive features and functions, what would you do differently or additionally? Assignment Link: http://book.visualisingdata.com/chapter/chapter-7 Assignment Length (word count): At least 550 words (not including direct quotes). References: At least three peer-reviewed, scholarly journal references.
CIS 510 Strayer University Project Risk and Feasibility Essay
Considering that enterprise system implementations fail 40 percent of the time, there is substantial risk involved—risk ...
CIS 510 Strayer University Project Risk and Feasibility Essay
Considering that enterprise system implementations fail 40 percent of the time, there is substantial risk involved—risk that, in many cases, can put a company out of business.Research project risk and feasibility. For each of the following risk categories, discuss:What the type of risk is.Ways to help mitigate the risk category.Examine your current place of work, or an organization of your choice, and write a paper in which you discuss:Organizational Risks.Technical Risks.Resource Risks.Schedule Risks.Use at least three quality resources. Note: Wikipedia and similar websites do not qualify as quality resources.This course requires the use of Strayer Writing Standards. For assistance and information, please refer to the Strayer Writing Standards link in the left-hand menu of your course.The specific course learning outcome associated with this assignment is:Assess the risks and mitigation strategies that are common to enterprise system implementations.
Information Gathering or Data Collection Discussion and Responses
Textbook :( I DONT HAVE THE TEXTBOOK)
Sharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial ...
Information Gathering or Data Collection Discussion and Responses
Textbook :( I DONT HAVE THE TEXTBOOK)
Sharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support 11E. ISBN: 978-0-13-519201-6
Create a discussion thread (with your name) and answer the following question:
Discussion (Chapter 6): List and briefly describe the nine-step process in con-ducting a neural network project.
Post
hey can you give replies to these 2 posts of my peers , as its part of the question. thanks1) Like any other project, conducting an artificial neural network requires preparing the data and the tools necessary to efficiently and accurately produce a desired product. According to Sharda et al (2020),the first step in the process of conducting an ANN project is gathering the data needed, arranging data to make sure that it is suitable for the ANN, and mold it into usable formats. The second step involves grouping data in the right clusters or training sets and validating the data(Sharda et al.,2020). Once the suitable data is ready, the next step is deciding on which network architecture will be used, and an appropriate learning algorithm is selected (Sharda et al.,2020). According to Sharda et al (2020) the fifth step involves customizing or tuning the parameters for the intended network and initializing the weights. Each neural network requires a specific data application, therefore, Sharda et al(2020) pointed out that the once the weights and the parameters are initialized, the next step is to transform the data into formats that are appropriate for the desired ANN.In step seven and eight, the input data and the desired output from the training sets are introduced to the ANN, and the neural network adjusts the weights in order to produce a desirable output (Sharda et al.,2020). After the weights have been adjusted, the created and tested neural network is deployed and used on new input data, in order to produce a different desired output and decision makers can decide if the right ANN was produced, and they would suggest modifications if deemed necessary (Sharda et al.,2020).ReferenceSharda, R., Delen, D., Turban, E. (2020). Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support 11E. ISBN: 978-0-13-519201-62) Neural Network Project
Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than a replica of how the brain functions (Sharda et al., 2020).
Step 1: Collect, organize, and format the data: The data to be used for training and testing the networks are collected. Important considerations are that the particular problem is amenable to a neural network solution and that adequate data exist and can be obtained (Turban et al., 2014).
Step 2: Separate data into training, validation, and testing sets: The training data must be identified, and a plan must be made for testing the performance of the network.
Step 3: Decide on network architecture and design: A network architecture and design are selected. The availability of a particular development tool or the capabilities of the development personnel may determine the type of neural network to be constructed (Turban et al., 2014).
Step 4: Select a learning algorithm: A learning method is selected. Important considerations are the exact number of neutrons and the number of layers. Some packages use genetic algorithms to choose the network design (Turban et al., 2014).
Step 5: Set network parameters and initialize their values: It is followed by the modification of the parameters as training performance feedback is received.
Step 6: Initialize weights and start training: This may also require writing software to preprocess the data or performing these operations directly in an ANN package (Turban et al., 2014).
Step 7: Stop training, freeze the network weights: The network computes the outputs and adjusts the weights until the computed outputs are within an acceptable tolerance of the known outputs for the input cases (Turban et al., 2014).
Step 8: Test the trained network: It is conducted iteratively by presenting input and desired or known output data to the network.Step 9: Deploy the network for use on an unknown new case: Now, the network can produce the desired outputs.ReferencesSharda, R., Delen, D., & Turban, E. (2020). Analytics, Data Science, & Artificial Intelligencesystems for decision support, global edition. Place of publication not identified: PEARSON EDUCATION Limited.Turban, E., Sharda, R., & Delen, D. (2014). Decision support and business intelligence systems.Harlow, Essex: Pearson.1
5 pages
Harassment Stalking
1. The use of a password is one of the most common modes of security protection system around the world with 99% of all mo ...
Harassment Stalking
1. The use of a password is one of the most common modes of security protection system around the world with 99% of all mobile and computer ...
Explain KPIs as they relate to web analytics
Assignment Instructions:Explain KPIs what are they, as they apply to web analytics.Explain your position if you agree or d ...
Explain KPIs as they relate to web analytics
Assignment Instructions:Explain KPIs what are they, as they apply to web analytics.Explain your position if you agree or disagree with their relevance in web analytics.Explain your position.Class: You may find newer and older resources listed each week in the Lessons and Assignments; however, the older resources are still relevant in content and concept. The relevancy is noted in that they build on the structural foundation of web analytics. We must be aware that Web Analytics is always in motion, and organizations are seeking to create actionable insights driving the decision making process.Class, please feel free to explore your own research for eBooks, journals and articles that best answer the topics and assignments. Do your best to locate resources that are no more than three (3) years old. DO NOT USE WIKIPEDIA AS A RESOURCE AND OR REFERENCE.Unoriginal Content:Your essay may contain no more than 1% quotes from other sources. Paraphrase what you read instead of copying and pasting. You may not re-use work that you have submitted in previous classes. All work in this class must be original.Essays that contain more than 20% unoriginal content will not earn any credit. Essays that contain between 3% - 19% unoriginal content will receive a substantial point deduction. Paraphrase instead of copying and pasting. Please note there is a difference between unoriginal content and plagiarism. Unoriginal content is correctly quoted and cited. Plagiarized sentences and paragraphs are not correctly quoted or cited. Plagiarism will result in an automatic zero for this assignment.Helpful Assignment Articles Web Links and Readings:KPI Example PDF Report2014: Top 5 Google Analytics KPIs: A Beginner’s Guide to Web Analyticshttp://www.datapine.com/blog/top-5-google-analytics-kpis/2012: http://www.kaushik.net/avinash/measure-choose-smarter-kpis-incentives/2011: http://www.kaushik.net/avinash/best-web-metrics-kpis-small-medium-large-business/2010: http://www.kaushik.net/avinash/web-analytics-101-definitions-goals-metrics-kpis-dimensions-targets/2009: http://www.kaushik.net/avinash/insights-web-analytics-kpi-measurement-techniques/
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