Consider the following set of data points (Year of experience salary). Find the 2^nd order polynomialand using polynomial regression determine the salary w

hen year of experience is

Explain working of SVM algorithm with the help of a suitable example.

Using the following training dataset, apply Naïve Bayes classification algorithm to find the class of an unknown sample X = < Rainy, Cool, High, False >

Explain K-Nearest Neighbour (K-NN) classification algorithm with the help of a suitable example

Briefly discuss the various Ensemble Methods.

In a class, three students tossed one coins (one each) for 3 times. Write down all the possible outcomes which can be obtained in this experiment. What is the probability of getting 2 or more than 2 heads at a time? Also find the probability of getting three tails at a time.

Define a frame for the entity date which consists of day, month and year. each of which is a number with restrictions which are well-known. Also, a procedure named compute-day-of-week is already defined.

Consider the following Minimax game tree search in which root is maximizing node and children are visited from left to right. Find the value of the root node of the game tree?

What are Intelligent agents in AI? Briefly discuss the properties of Agents. Q5: Find the minimum cost path for the 8-puzzle problem, where the start and goal state are given as follows:   

Start State

Goal State

Compare Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).

What is Turing Test? What is the Criticism to the Turing Test?

Compare ANI, AGI and ASI, in context of AI. Also, discuss the major applications of AI.

What is the Random Forest algorithm? Explain how it can be applied to classification problems. Write a program in R to implement a Random Forest classifier on a sample dataset and explain its output.

Discuss the challenges of online advertising and recommendation systems. Explain the concept of collaborative filtering with an example, and discuss the role of clustering in social network analysis.

What is the PageRank algorithm, and how is it used in link analysis? Describe the concept of “flow of rank” in PageRank. Explain how the PageRank of a web page is calculated using the flow model.

Describe the purpose and functionality of a Bloom filter in data stream processing. How does the Bloom filter efficiently check for element presence? Describe the Flajolet-Martin algorithm for cardinality estimation in data streams.

Compare Apache Spark, Hive, and HBase in terms of functionality, data processing methods, and use cases. When would Spark be preferred over traditional MapReduce, and why?

Explain the Hadoop architecture with a focus on HDFS and the master/slave architecture. How do NameNode and DataNodes work together to store and manage large datasets? Provide a basic example of this storage process.

Discuss the 4 Vs of big data (Volume, Velocity, Variety, and Veracity). Provide a real-world example of each, explaining how these characteristics create challenges in big data management.

Describe the role of statistical hypothesis testing in data analysis. What are Type I and Type II errors, and how do they affect decision-making? Provide an example of hypothesis testing in a real-world scenario.