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Data Engineering

The reading involves the application of skip-gram models to enrollment sequences

The reading involves the application of skip-gram models to enrollment sequences to learn and explore relationships in a course vector space.
You will have 40 minutes to finish once started. It consists of four short essay questions and one matching question.

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Data Engineering

Data Science with Excel and Fortran 95. You are going to deliver two files; 1- t

Data Science with Excel and Fortran 95.
You are going to deliver two files; 1- the completed version of the program as YourName_Assignment09.f95, and 2-The excel file of your results as YourName_output.xlsx.

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Data Engineering

https://www.meng.ucla.edu/data-science/ I’ve have a brief content of my previous

Data Science


I’ve have a brief content of my previous experience. Please add 250-300 words about the following content: 1.why your past achievements have stimulated your desire for graduate studies?
2. Describe your research in this program 3. how graduate school will help you reach your
career goals
4. as well as the contribution you will make to the program.

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Data Engineering

Write a hive query to find all the stocks symbols whose closing price is larger than your age.

1. Load the large stocks dataset (400 MB) into HDFS and use the dataset to create a Hive table using the location attribute.
2. Write a SQL command to find the stocks with average daily volume larger than 1 million shares.
3. Write a Hive query to find the top 3 stocks by volume for the year 2004.
4. Write a Hive query to find the top 3 stocks by volume and whose symbol start with the first letter of your name (example for Saber, it is symbols starting with “S”).
5. Write a Hive query to find all the stocks symbols whose closing price is larger than your age.
6. Write a Hive query to find the top 10 stocks with largest intraday price change (difference between high and low price during a trading day) and also display the amount of the change.

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Data Engineering

Density Estimation

Topics are: 1) Density Estimation
2) PDA
3) KNN
4) Linear and Logistic Regression
5) PCA
6) Clustering
7) Decision trees
8) K – means
the calculations will be from the above topics. be sure to conversant with the above topics.

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Data Engineering

● List and describe the type of data you will need for your application, and how you will ensure the quality of the data.

Imagine your organization is going to build an application utilizing Big Data and Machine Learning. You are going to propose your idea to upper management with supporting system design. Develop an APA-formatted paper that presents a detailed analysis and research-based information pertaining to ALL of the following topics
● List and describe the type of data you will need for your application, and how you will ensure the quality of the data.
● List and explain the technologies, tools, and software packages that will be used to build the application.
○ Provide the design of your Big Data database. Explain why you chose the database compared to others. Also, include supporting theories for the schema you came up with.
○ Describe in detail why the chosen technologies are adequate to process the data.
○ List and describe the types of the statistical analysis methods that will be used.
● List and describe the benefits from the customer’s perspective and organization’s perspective. Please pinpoint where the benefits are drawn from – data, technology, software package, process, and etc.
● List and describe the concerns and downsides that may be introduced by the application and the Big Data from multiple perspectives – law, regulations, social, etc. Provide solutions, processes, application modules, etc. that mitigate the concerns, problems, issues.
● Provide a data flow diagram, database design, and sample code of a module for your application.
6 pages

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Data Engineering

Density Estimation

Topics are: 1) Density Estimation
2) PDA
3) KNN
4) Linear and Logistic Regression
5) PCA
6) Clustering
7) Decision trees
8) K – means
the calculations will be from the above topics. be sure to conversant with the above topics.

Categories
Data Engineering

L. M. Sacasas, “Resistance is Futile: The Myth of Tech Inevitability (Links to an external site.),” The Convivial Society, Vol. 2, No. 7 (Substack), 21 April 2021.

Please copy the following “Reading Notes Form” into a new document and fill it out for each of the assigned readings for the week. Submit as a single Word or PDF document. Due the night before your section at midnight (so, if your section meets on Tuesdays, for example, your reading notes will be due each Monday before midnight).
L. M. Sacasas, “Resistance is Futile: The Myth of Tech Inevitability (Links to an external site.),” The Convivial Society, Vol. 2, No. 7 (Substack), 21 April 2021.
L. Winner, “Do Artifacts Have Politics?” Daedalus, 109 (1): 121-136 (Winter 1980)
Back to Unit 1
Atttachment:
https://theconvivialsociety.substack.com/p/resistance-is-futile-the-myth-of

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Data Engineering

Describe the two key abilities brought by the data discovery technology.

Describe the two key abilities brought by the data discovery technology.
● List and explain types of data flaws and techniques and methodologies used to mitigate the risks that may be introduced by the flaws of the data and make data more meaningful to organizations.
● List and demonstrate the types of the data applicable to different industries by looking at successful case studies of well-known organizations.
need 4 pages on this by Thursday, Attach plagiarism report

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Data Engineering

Learning Goal: I’m working on a data engineering test / quiz prep and need an ex

Learning Goal: I’m working on a data engineering test / quiz prep and need an explanation and answer to help me learn.You are going to work on two functions. In the first function you need to generate n-grams based on the value of n given by the user. In the second function, you need to send the word or words sequence to the function and your function should predict and return the next word with high frequency of occurances.Q1: Please complete the function get_Ngrams. This function will take the text and the value of n and will return the n-grams based on that. Q2: Your task here is to complete the function predictNextWord, that will take the text and the words sequence. Your function should predict the next word in the words sequence with the highest frequency.