machine learning
Q: Is Mass Hysteria Driving the Big Data Market? What are the two pros and two cons of the emerging…
A: Big data market is affecting the businesses like a wildfire.Slowly recovering businesses feel…
Q: OLAP can be used to analyze descriptive analytics. Computer science
A: Answer: To understand how OLAP technology helps with business intelligence (BI), we must first…
Q: Q3) Deep learning a) Explain the concept of 1x1 convolutions and how it can be used? b) Explain the…
A: Answer A:- A 1x1 convolution simply maps an input pixel with all it's channels to an output pixel,…
Q: How is Big data sets era of AI different from 50 years ago?
A: When we say BIG DATA, I think many of us think that It is a kind of big amount or size of data yeah,…
Q: What are Barry Boehm's thoughts on the spiral model in the context of system analytics?
A: Given: What are Barry Boehm's ideas on the spiral model in system analytics?
Q: What is the Universal data model?
A: Universal Data Model provides the information model that allows different Software products to…
Q: Distinguish between the functions of OLAP and descriptive analytics.
A: The answer is given below.
Q: How is the era of AI different from 50 years ago in terms of big data sets?
A: Artificial intelligence algorithms are created to make judgments based on data that is often updated…
Q: Is data visualization just beneficial when dealing with large amounts of information? Extend and…
A: The display of data is beneficial not just for big data, but also for other fields.
Q: nformation technology What are the advantages and disadvantages of scattered data processing that…
A: Introduction: Dispersed processing has a number of advantages.
Q: How does data literacy apply to career and ethics?
A: According to the information given:- We have to explain how the data literacy apply to career and…
Q: How might data literacy be applied to the workplace or to ethical decision-making?
A: literacy : We must explain how data literacy applies to career and ethics, based on the facts…
Q: a) Explain the concept of 1x1 convolutions and how it can be used? b) Explain the concept of data…
A: Answer:- A 1x1 convolution simply maps an input pixel with all it's channels to an output pixel,…
Q: What is the connection between datasets and data literacy?
A: Introduction: The connection between different datasets and information literacy:
Q: Distinguish how OLAP functions in descriptive analytics.
A: Introduction: Even while OLAP engines make it easy to do operations such as slicing, dicing,…
Q: True or False? Why? b. Decision trees or Naive Bayes produce more understandable and interpretable…
A: b. True c. True d. False
Q: what would be the impact on the overall knowledge discovery if you analyse a dataset having corrupt…
A: Data is said to be corrupt if it looses it's originality and causes error.
Q: Describe the Linear regression technique used for prediction with necessary mathematical analysis.
A: GIVEN: Describe the Linear regression technique used for prediction with necessary mathematical…
Q: Big Data presents what kinds of ethical problems?
A: To be determine: Big Data presents what kinds of ethical problems?
Q: Who would need the various kinds of meta-data and why? (Ponniah's chapter on meta data).
A: Given: Who would need the various kinds of meta-data and why? (Ponniah's chapter on meta-data).
Q: 2-How is data organized and analyzed in the Zachman framework?
A: Answer: ZACHMAN FRAMEWORK is not a conventional method that follows a series of steps to be follwoed…
Q: Use accurate data. Briefly explain machine learning and deep learning in few lines.
A: According to the given question, it is required to briefly explain machine learning and deep…
Q: "Treat other's data as vou would have others treat your data." Justify the given maxim with 5Cs of…
A: The answer is
Q: Summarize the Working with Data tutorials in your own words. Use critical thinking and an academic…
A: Introduction: The process of running Structured Query Language (SQL) in a database software is known…
Q: Compare and contrast data mining, machine learning and artificial intelligence
A: Data mining: The objective of data mining is to find beforehand concealed examples and connections…
Q: Q: Information today comes in different forms. Explain those forms with the help of examples in…
A: Data communications (DC) is the process of transferring data from one location to another or among…
Q: Describe the Linear regression technique used for prediction with necessary mathematical analysis.…
A: Given: Describe the Linear regression technique used for prediction with necessary mathematical…
Q: in the next 10-20 years, express your prediction of data science. it can be in the field of…
A: Data Science will have a huge impact on business and society in the next 10-20 years. It will change…
Q: Give a True or False answer, as well as an explanation. In the Big Data universe, Spark has…
A: Introduction: Spark is a data processing engine that is built on the Java Virtual Machine (JVM) that…
Q: Give a scenario/situation where data preprocessing is used? Discuss its impact on the situation.
A: Give a scenario/situation where data preprocessing is used? Discuss its impact on the situation.…
Q: What is A/B testing in Data Science?
A: Introduction: Bucket testing and split testing are other terms for A/B testing. This is the process…
Q: Explain the link between AI, Data Analysis and Economic Relationships, and connect this to the…
A: INTRODUCTION: Artificial intelligence (AI) has the potential to alter international trade. AI's…
Q: what is perception in data science? (detailed definition with example)
A: Data Science is the field of study that combines domain expertise, programming that knowledge of the…
Q: Examine how technology affects health-care data systems.
A: The following are the primary effects of technology on the healthcare information system:…
Q: How well are the contexts of data sources remembered and represented
A: Introduction: A DataSource is the name given to a link established on a website from a server. When…
Q: a) What is the confusion matrix? b) Why accuracy is not enough to evaluate the performance of an Al…
A: Confusion matrix: A confusion matrix is a matrix that is commonly used to evaluate a classification…
Q: What is the difference between "data mining" and "OL
A: Acually, the difference is given below; between "data mining" and "OLAP"
Q: down the role of decion tree in datascience?
A: Actually, given question regarding data science
Q: What's the difference between EDA and hypothesis testing, and why may analysts favor EDA when data…
A: INTRODUCTION: EDA: It is the process of examining a dataset to identify patterns and outliers…
Q: Understanding the distinction between EDA and hypothesis testing, as well as why analysts may favor…
A: Introduction: EDA stands for exploratory data analysis, which refers to preliminary data analysis…
Q: When classifying data, when should we use the Nave Bayes approach, and when should we avoid it?
A: When to implement the Naive Bayes Algorithm When there are few training data points. In the course…
Q: data mining- What is the scope of business intelligence and why are BI technologies necessary?
A: Introduction: Business intelligence (BI) is defined as follows:
Q: The difference between EDA and hypothesis testing, as well as why analysts may prefer EDA over…
A: Introduction: An examination of a hypothesis would contain a description of the specifics of the…
Q: "Bigtable's data model is essentially like a very large three dimensional spreadsheet". Enter your…
A: - We can answer the first question only as per our guidelines. - We need to validate the statement…
Q: Total cluster for today: 2 Final report of Covid-19 cases for today: disctrict total cases remarks…
A: Introduction An array is a linear data structure that can store the values in a fixed size…
Q: Explain Google Colab. Use Python and any dataset of your choice and explain one example…
A: Google colab is a free tool that combines Jupyter notebook , cloud and google drive. It is a data…
Q: Explain how the three properties of big data (volume, velocity, and variety) apply to the data…
A: Introduction: The three characteristics of bi data are Volume, Velocity, Variety. They are the…
4-What would you guess a training example in the M-NIST dataset would look like?
5-Can you name some of the major categories of machine learning?
6-When would you guess machine learning was invented?
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