Why we talk about about Predictive, Diagnostic and Prescriptive is also in domain Machine Learning?

Q: Machine learning is an empirical subject," says the source of the aforementioned quote. What exactly…

A: Machine Learning: Machine learning studies algorithmic learning. Machine Learning focuses on using…

Q: In the context of Machine Learning explain the following in your own words. 1. Explain the purpose…

A: Supervised learning                  Unsupervised learning In supervised learning,…

Q: 6. Discuss this relationship between supervised learning and reinforcement learning.

A: Answer:  Both are Comes under in machine learning. In Supervised learning both input and output will…

Q: That is the man or woman who came up with the idea of ADTs? Describe them. How are they put into…

A: Overview: Abstract data type (ADT) is a mathematical construct that is used to describe a variety of…

Q: Compare case-based versus model-based reasoning in-depth, and provide instances of each method's…

A: Case-Based Reasoning: A paradigm of the artificial intelligence and cognitive science known as…

Q: Critically compare case-based and model-based reasoning and mention their respective application…

A: Below i have answered:

Q: descriptive models are preferable than prescriptive models; nevertheless, which one is better?

A: Descriptive model:- A descriptive model is a mathematical model which describes the entity or the…

Q: Give 3 examples each for Declarative Knowledge and Procedural Knowledge.

A: Your answer is given below.  Introduction :- Declarative Knowledge :- Declarative Knowledge…

Q: t true that algorithms and data structures are no longer utilized in this day and age of machine lea

A: Required: To explain whether it is true that algorithms and data structures are no longer utilized…

Q: In general, descriptive models are preferable than prescriptive models; nevertheless, which one is…

A: Languages ​​and grammar rules are closely linked, naturally adapting to their circumstances, and…

Q: 3.Talk about the consequences of overfitting and underfitting.

A: The answer for the given question is given below:

Q: what kind of calculations can we expect AI to be used exclusively under the guidance of humans in…

A: It is defined as a wide-ranging tool that enables us to more effectively integrate information,…

Q: We use machine learning when certain models must be customized. True or False (A) True B) False

A: It is defined as a branch of artificial intelligence and computer science which focuses on the use…

Q: Explain in your own words unsupervised machine learning and compare it with supervised machine…

A: Given: Explain in your own words unsupervised machine learning and compare it with supervised…

Q: What does "predictive analysis" mean? Give a use example f

A: Predictive analytics is the use of data to predict future trends and events. It uses historical data…

Q: Which is not a property of representation of knowledge? (a) Representational Verification (b)…

A: Question. Which is not a property of representation of knowledge? (a) Representational Verification…

Q: Do imperfect and am

A: Introduction: Reasoning is the process of arriving at logical conclusions and making predictions…

Q: Why are we discussing Predictive, Diagnostic, and Prescriptive Machine Learning?

A: Analytical descriptive methods include gathering, organizing and presenting historical data such…

Q: Explain briefly what supervised, unsupervised, and reinforcement learning are.

A: Please find the answer in next step

Q: Compare and contrast Supervised and Unsupervised Machine learning by filling the table below.…

A: The availability of ground truth information is crucial to supervised learning. A ground truth is a…

Q: QUESTION: Propose the knowledge representation (KR) for the Lane Detection Project, and also provide…

A: Answer: 1. Logical Representation A language with certain specific principles that deal with…

Q: ucial. Is it possible to skip this phase by employing formal methods? Explain the importance of…

A: Is it possible to bypass the testing phase if formal methods are used?Without skipping a single…

Q: Do imperfect and ambiguous models pose a challenge to non-monotonic reasoning?

A: Solution for do imperfect and ambiguous models pose a challenge to non monotonic reasoning

Q: What is the best way to model an artificial intelligence system using functional decomposition?

A: Answer:

Q: Do you see yourself using email in the not-too-distant future? The path of an email message starts…

A: Introduction: Once an email has been sent, the message is sent to the Mail Transfer Agent (MTA) via…

Q: Are data structures and algorithms outmoded in the era of Machine Learning? What explains their…

A: Introduction   Answer: Data structures and Algorithms are not obsolete. Because it is the foundation…

Q: Discuss the application of deep learning models in the following fields: a. Predictive analysis. b.…

A: We use historical data to forecast future outcomes in predictive analysis. As a result, predictive…

Q: In your own words describe the differences between the terms artificial intelligence (AI), machine…

A: According to your question Artificial Intelligence (AI) is a common term that combines Machine…

Q: Why do we discuss Predictive, Diagnostic, and Prescriptive in the context of Machine Learning?

A: Given: Why do we discuss Predictive, Diagnostic, and Prescriptive in the context of Machine…

Q: Compare case-based versus model-based reasoning in-depth, and provide instances of each method's us

A: Introduction Compare case-based versus model-based reasoning in-depth, and provide instances of each…

Q: Demonstrate your understanding of machine learning. When it comes to machine learning, how can you…

A: Machine learning: Machine learning is a method used in artificial intelligence that enables…

Q: How would you explain Machine Learning in layman’s term? You can use simple examples to explain it.

A: Layman's terms states that anything should be explain in simple terms that anybody having no…

Q: ne Learning question : a) Elaborate what is the meaning of hyperparameter tuning and why it is…

A: Q1  A model hyperparameter is a configuration that is external to the model and whose value cannot…

Q: In what ways are prescriptive models different from descriptive models?

A: Here there are multiple questions given, so i answered question 1 below. If you want any other…

Q: Q1/Explain to me in detail what is the advantages and disadvantages of a machine learning in…

A: Machine learning (ML) Machine learning is the study of computer algorithm that improve the…

Q: 3. Answer the following questions about supervised learning: (a) What is the difference between…

A: Given: What are the distinctions between parametric and nonparametric models?

Q: Give an account of the five AI-related fields where fuzzy logic has been successfully implemented so…

A: This question explicitly addresses the AI applications of fuzzy Logic.  It is primarily a…

Q: Identify the form of hypothesis in the following statement?  The proposed system decreases the…

A: The  alternative hypothesis always contradict the actual statement.inside the bracket it is…

Q: Explain the concept of machine learning. What is the difference betwegn supervised and unsupervised…

A: Given: Explain the concept of machine learning. What is the difference betwegn supervised and…

Q: In what ways are descriptive models and prescriptive models distinct from one another? a.

A: Introduction: A descriptive model is used to describe the relationship between a system or other…

Q: Question 1 (20 marks) The Ghana health service requested for a machine learning model to detect the…

A:

Q: Subject - Machine Learning What is  Lexicon-based / attention neural networks based approach model…

A:

Q: Define and explain (i)  Supervised learning (ii)  Unsupervised learning (iii)  Reinforcement…

A: Note: As per our company guidelines we are supposed to answer only first 3 sub-parts. Kindly repost…

Q: (1) What is the difference between Machine Learning based systems and Rule based systems? (6 Points)

A: Machine learning is anything but artificial intelligence which is allowing software to become higher…

Q: Discuss any four serious challenges in machine learning, specifically when working with textual…

A: Machine learning is a method of data analysis that automates analytical model building. it is a…

Q: What have you learned about machine learning that surprises you? Give an example of a situation…

A: The answer is given below:-

Q: n trees, Neural Network and SVM on the “Adult” Dataset and Compare the models parameters w.r.t to…

A: It is defined as a general, predictive modelling tool that has applications spanning a number of…

Q: Differentiate between supervise learning and unsupervised learning in context of machine learning.…

A: Supervised Learning:- It is type of machine learning algorithms which maps input into output by…

Q: Can the exclusive or (XOR) connective be learned by simple neural networks/perceptrons?

A: Here  is the solution:

Q: Which of the following were mentioned as possible issues with current machine learning technology?…

A: According to the information given:- we have to find the possible issues with current machine…

Q: 7. Which kind of quantitative research investigates a possible relationship between previous events…

A: The quantitative design is based in the scientific method and it uses deductive reasoning, where the…

Q: In this discussion, we will look at five specific applications of fuzzy logic found in artificial…

A: Given: This question directly deals with the uses of Fuzzy logic in AI. It is primarily a…

Q: Is it possible to train machine learning models using log data

A: False  Human-based log analysis can be slow and painful. Instead, machine learning can be used to…

Q: Is it feasible to differentiate between descriptive and prescriptive models by looking at the…

A: Introduction: The link between a system or other entity and its environment is explained using a…

Q: Discuss the three Variations of Case-Based Reasoning (CBR)?

A: According to the information given:- We have to discuss the 3 variation of Case-Based Reasoning…

System Model Approaches

The systems model approach is a process-oriented representation that emphasizes the impact or flow of information between modules. The multidisciplinary study of the use of models to design and create systems in business and IT development is known as systems model approach. It models how processes interact and what these processes do, but it does not go into detail about how these processes are implemented. Functional decomposition may be utilized to enhance the models employed in this technique, and they can be coupled to requirements models for additional system partitioning.