week 1 assignment answers

Introduction To Internet Of Things | NPTEL | Week 1 Assignment Solutions

This set of MCQ(multiple choice questions) focuses on the  Introduction To Internet Of Things NPTEL Week 1 Assignment Solutions .

Course layout (All week answers link)

Week 0 Week 1 : Introduction to IoT Week 2: Basics of Networking Week 3: Communication Protocols Week 4:   Sensor Networks Week 5:   Interoperability in IoT Week 6: Introduction to Python programming Week 7:   Implementation of IoT with Raspberry Pi (contd), Introduction to SDN, SDN for IoT Week 8:   SDN for IoT (contd), Data Handling and Analytics, Cloud Computing Week 9 :  Cloud Computing(contd), Sensor-Cloud Week 10:  Fog Computing, Smart Cities and Smart Homes Week 11: Connected Vehicles, Smart Grid, Industrial IoT Week 12: Industrial IoT (contd), Case Study: Agriculture, Healthcare, Activity Monitoring

NOTE:  You can check your answer immediately by clicking show answer button. Moreover, this set of “Introduction To Internet Of Things NPTEL Week 1 Assignment Solution” contains 15 questions.

Now, start attempting the quiz.

Introduction To Internet Of Things NPTEL Week 1 Solutions

Q1. Which of the following are the enablers of IoT?

a) RFID b) Nanotechnology c) Sensors d) All of these

Answer: d) All of these

Q2. Which of the following is/are NOT a characteristic of IoT?

a) Efficient, scalable and associated architecture. b) Ambiguous naming and addressing. c) Abundance of sleeping nodes, mobile and non-IP devices. d) None of these

Answer: b) Ambiguous naming and addressing.

Q3. State whether the following statement is True or False. Statement: The increasing number of devices in IoT is expected to result in an address crunch.

a) True b) False

Answer: a) True

Q4. State whether the following statement is True or False. Statement: The gateway has a unique network prefix, which can be used to identify them globally.

Q5. Sometimes, when there is a need for the nodes to communicate directly to the Internet, ______________ can be used.

a) Sensors b) Actuators c) Tunneling d) None of these

Answer: c) Tunneling

Q6. In _______________ a node/network is connected to multiple networks for improved reliability.

a) Transparent roaming b) Multi-homing c) None of these d) Both a) and b)

Answer: b) Multi-homing

Q7. The IPv6 notation uses ___________________ values.

a) Roman b) Hexadecimal c) Both a) and b) d) None of these

Answer: b) Hexadecimal

Q8. A _____________ detects (senses) changes in the ambient conditions or in the state of another device or a system, and forwards or processes this information in a certain manner.

a) Sensor b) Actuator c) Both a) and b) d) None of these

Answer: a) Sensor

Q9. A microphone is an example of an _____________.

a) Input device and actuator b) Only actuator c) Only Transducer d) Input device and transducer

Answer: d) Input device and transducer

Q10. The ________________ of a sensor is the smallest change it can detect in the quantity that it is measuring.

a) Resolution b) Bias c) Noise d) None of these

Answer: a) Resolution

Q11. Based on the data type, sensors are classified as _______________________.

a) Scalar and Vector/Multimedia b) Only scalar c) Both a) and b) d) Only vector

Answer: a) Scalar and Vector/Multimedia

Q12. Solenoid valve is an example of ______________________.

a) Sensor b) Actuator c) Processing unit d) None of these

Answer: b) Actuator

Q13. An actuator requires a ______________________ and ______________________.

a) Control signal and a bias signal b) Control signal and a source of energy c) Noise signal and a source of energy d) None of these

Answer: b) Control signal and a source of energy

Q14. State whether the following statement is True or False. Statement: Pneumatic rack and pinion actuators are used for valve controls of water pipes.

Q15. Which of the following is NOT a function of an IoT gateway?

a) Switching b) Routing c) Protocol conversion d) Generating noise

Answer: d) Generating noise

Introduction To Internet Of Things NPTEL 2022 Week 1 Assignment Solutions

Q1. Which of the following is/are the characteristics of IoT?

a) Efficient, scalable and associated architecture. b) Unambiguous naming and addressing c) Abundance of sleeping nodes, mobile and non-IP device d) All of these

Q2. A _________ allows us to use our smartphones to lock and unlock our do our homes or our businesses.

a) Smart Meter b) ATM c) Digital Lock d) Web

Answer: c) Digital Lock

Q3. The function/functions of an IoT Gateway is/are to?

a) Forward packets between LAN and WAN and on the IP layer b) Connect IoT LAN to a WAN c) Both a) and b) d) None of these

Answer: c) Both a) and b)

Q4. Multi-homing is the concept where a node can be connected to multiple networks for ____________.

a) Reduced Reliability b) Improved Reliability c) None of these d) Both a) and b)

Answer: b) Improved Reliability

Q5. A Passive Infrared Ray (PIR) sensor is used for ____________?

a) Humidity Detection b) Tilt Detection c) Obstacle Detection d) Smoke Detection

Answer: c) Obstacle Detection

Q6. For which of the following, Vector Sensors are required to measure or sense them?

a) Color, Pressure, Temperature b) Orientation, Image c) None of these d) Both a) and b)

Answer: b) Orientation, Image

Q7. The sensitivity of a sensor under real conditions may differ from the value specified. This is called __________?

a) Maximal Error b) Minimal Error c) Median Error d) Sensitivity Error

Answer: d) Sensitivity Error

Q8. A random deviation of the signal that varies in time is called ______________.

a) Noise b) Sound c) Bias d) None of these

Answer: a) Noise

Q9. A Relay Switch is an example of _______________.

a) A Sensor b) An Actuator c) A Transducer d) None of These

Answer: b) An Actuator

Q10. What is a Pneumatic Actuator?

a) It is a type of actuator driven by compressed air or vacuum b) It is a type of actuator driven by fluid c) It is a type of actuator driven by solid d) None of these

Answer: a) It is a type of actuator driven by compressed air or vacuum

Q11. Which type of actuators tend to be compact, lightweight, economical, and with high power density?

a) Thermal or Magnetic Actuators b) Hydraulic Actuators c) Both a) and b) d) None of these

Answer: a) Thermal or Magnetic Actuators

Q12. Polymer based actuators designed to handle fragile objects like fruit harvesting in agriculture or manipulating internal organs in biomedicine are called?

a) Pneumatic Actuators b) Soft Actuators c) Software Actuators d) Hardware Actuators

Answer: b) Soft Actuators

Q13. Full form of SMP is ____________?

a) Soft Memory Polymer b) Shape Memory Polymer c) Software Memory Polymer d) None of these

Answer: b) Shape Memory Polymer

Q14. Duty Cycling of the sensors is managed by which component of IoT?

a) Application b) Real-Time Kernel c) Radios d) Power Management Unit

Answer: d) Power Management Unit

Q15. Which of the following are challenges of IoT?

a) Security b) Complexity Management c) Modeling and Analysis d) All of these

Previous Year – Introduction To Internet Of Things NPTEL Week 1 Assignment Solutions

Q1. Which of the following is a static mechanism for address allocation of IoT nodes?

a) Configuration over a management interface b) IPv6 address based on a hardware identifier c) Both configuration over a management interface & based on a hardware identifier d) IoT nodes can’t be configured statically

Answer: c) Both configuration over a management interface & based on a hardware identifier

Q2. Which of the following error is commonly found in heating of metal strips?

a) quantization error b) aliasing error c) hysteresis error d) None of these

Answer: c) hysteresis error

Q3. Identify the component shown below:

a) Gas sensor b) PIR sensor c) Light sensor d) Speaker

Answer: b) PIR sensor

Q4. “X” performs active application layer functions between IoT nodes and other entities. What is X?

a) IoT node b) IoT proxy c) IoT gateway d) IoT Network

Answer: b) IoT proxy

Q5. Which of the following field in IPv4 header format indicates that it is concerned with reliable transmission?

a) Traffic class b) Hop limit c) Fragment offset d) Destination address

Answer: c) Fragment offset

Q6. Which of the following is a function of IoT Gateway?

a) Data forwarding b) Device management c) Protocol conversion d) All of these

Q7. Which of the following actuator converts pressure into force?

a) Mechanical actuators b) Pneumatic actuators c) Electric actuators d) Magnetic actuators

Answer: b) Pneumatic actuators

Q8. Which of the following mechanism for address autoconfiguration provide more control on the allocated addresses?

a) DHCPv6 b) SLAAC c) Both DHCPv6 and SLAAC d) None of these

Answer: a) DHCPv6

Q9. Which of the following can measure position?

a) Potentiometer b) Encoder c) Both potentiometer & encoder d) None of these

Answer: c) Both potentiometer & encoder

Q10. In a scenario when the IoT proxy has uplink connectivity, does the IoT LAN need global addressing mandatorily?

a) Yes b) No c) Not applicable

Answer: b) No

Q11. Which of the following is TRUE?

a) M2M is not a subset of IoT b) WoT and IoT are same c) IoT and M2M are same d) None of these

Answer: d) None of these

Q12. Statement I: Aliasing error occurs if the input variable or added noise changes periodically at a frequency proportional to the multiple of the sampling rate. Statement II: If the signal is monitored digitally, the sampling frequency can cause a dynamic error triggering aliasing error.

a) Both Statement I and II are false b) Both Statement I and II are true c) Statement I is false but Statement II is true d) Statement I is true but Statement II is false

Answer: b) Both Statement I and II are true

Q13. Does polymer-based actuator find application in manufacturing artificial muscles?

a) Yes b) No

Answer: a) Yes

Q14. Unique Local Addresses are intended to allow routing over a network that expands over multiple links and routing hops, and even can expand over multiple networks. Can these addresses prevent address collision?

a) Yes b) No c) Not Applicable

Q15. Which of the following is an example of vector sensor?

a) Pressure sensor b) Strain sensor c) Both pressure and strain sensors d) Sound sensor

Answer: d) Sound sensor

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NPTEL Introduction to Machine Learning | Week 1 Assignment Answer

Welcome to this comprehensive guide where I present the answers to the Week 1 assessment of NPTEL's Introduction to Machine Learning course. This course is designed to lay the groundwork for understanding the core concepts and methodologies that drive modern machine learning applications.

Machine learning, a cornerstone of artificial intelligence, empowers computers to learn from data and make informed decisions without explicit programming. Week 1 of this course focuses on foundational principles such as data preprocessing, exploratory data analysis (EDA), and statistical techniques essential for machine learning practitioners.

Throughout this post, I will meticulously address each multiple-choice question (MCQ) from the Week 1 assignment. The answers provided are meticulously crafted based on the rigorous study of course materials, ensuring accuracy and clarity in understanding fundamental ML concepts.

Whether you are a student aspiring to enter the field of data science, a professional seeking to enhance your skills, or an enthusiast curious about the intricacies of machine learning, this blog aims to serve as a valuable resource. By elucidating the rationale behind each answer, I aim to facilitate a deeper comprehension of machine learning fundamentals and their practical applications.

Here are Introduction to Machine Learning Week 1 Assignment Answers

Q1. Which of the following is/are unsupervised learning problem(s)?

• Grouping documents into different categories based on their topics
• Forecasting the hourly temperature in a city based on historical temperature patterns
• Identifying close-knit communities of people in a social network
• Training an autonomous agent to drive a vehicle
• Identifying different species of animals from images

Answer: A, C Grouping documents into different categories based on their topics Identifying close-knit communities of people in a social network

Q2. Which of the following statement(s) about Reinforcement Learning (RL) is/are true?

• While learning a policy, the goal is to maximize the long-term reward.
• During training, the agent is explicitly provided the most optimal action to be taken in each state.
• The state of the environment changes based on the action taken by the agent.
• RL is used for building agents to play chess.
• RL is used for predicting the prices of apartments from their features.

Answer: A, C, D While learning a policy, the goal is to maximize the long-term reward. The state of the environment changes based on the action taken by the agent. RL is used for building agents to play chess.

Q3. Which of the following is/are classification tasks(s)?

• Predicting whether an email is spam or not spam
• Predicting the number of COVID cases over a given period
• Predicting the score of a cricket team
• Identifying the language of a text document

Answer: A, D Predicting whether an email is spam or not spam Identifying the language of a text document

Q4. Which of the following is/are regression task(s)?

• Predicting whether or not a customer will repay a loan based on their credit history
• Forecasting the amount of rainfall in a given place
• Identifying the types of crops from aerial images of farms
• Predicting the future price of a stock

Answer: B, D Forecasting the amount of rainfall in a given place Predicting the future price of a stock

Q5. Consider the following dataset. Fit a linear regression model of the form y=β0+β1×1+β2×2 using the mean-squared error loss. Using this model, the predicted value of y at the point (x1,x2)=(0.5,−1.0) is:

• −0.651
• −0.737
• −0.872

Answer: −0.737

Q6. Consider the following dataset. Using a k-nearest neighbour (k-NN) regression model with k=3, predict the value of y at (x1,x2)=(0.5,−1.0). Use the Euclidean distance to find the nearest neighbours.

• −1.762
• −2.061
• −1.930
• −1.529

Answer: −1.930

Q7. Consider the following statements regarding linear regression and k-NN regression models. Select the true statements.

• A linear regressor requires the training data points during inference.
• A k-NN regressor requires the training data points during inference.
• A k-NN regressor with a higher value of k is less prone to overfitting.
• A linear regressor partitions the input space into multiple regions such that the prediction over a given region is constant.

Answer: B, C A k-NN regressor requires the training data points during inference. A k-NN regressor with a higher value of k is less prone to overfitting.

Q8. Consider a binary classification problem where we are given certain measurements from a blood test and need to predict whether the patient does not have a particular disease (class 0) or has the disease (class 1). In this problem, false negatives (incorrectly predicting that the patient is healthy) have more serious consequences as compared to false positives (incorrectly predicting that the patient has the disease). Which of the following is an appropriate cost matrix for this classification problem? The row denotes the true class and the column denotes the predicted class.

• [0 0 100 0]
• [0 1 100 0]
• [0 100 1 0]
• [0 100 0 0]

Answer: D. [0 1 100 0]

Q9. Consider the following dataset with three classes: 0, 1 and 2. x1 and x2 are the independent variables whereas y is the class label. Using a k-NN classifier with k = 3, predict the class label at the point (x1,x2)=(0.7,−0.8). Use the Euclidean distance to find the nearest neighbours.

• Cannot be predicted

Q10. Suppose that we train two kinds of regression models corresponding to the following equations. (i) y=β0+β1×1+β2×2 (ii) y=β0+β1×1+β2×2+β3x1x2 Which of the following statement(s) is/are correct?

• On a given training dataset, the mean-squared error of (i) is always greater than or equal to that of (ii).
• (i) is likely to have a higher variance than (ii).
• (ii) is likely to have a higher variance than (i).
• If (ii) overfits the data, then (i) will definitely overfit.
• If (ii) underfits the data, then (i) will definitely underfit.

Answer: A, C, E On a given training dataset, the mean-squared error of (i) is always greater than or equal to that of (ii). (ii) is likely to have a higher variance than (i). If (ii) underfits the data, then (i) will definitely underfit.

Introduction to Machine Learning - July-Dec 2023 Assignment Answers

Q1. Which of the following is a supervised learning problem?

• Grouping related documents from an unannotated corpus.
• Predicting credit approval based on historical data.
• Predicting if a new image has cat or dog based on the historical data of other images of cats and dogs, where you are supplied the information about which image is cat or dog.
• Fingerprint recognition of a particular person used in biometric attendance from the fingerprint data of various other people and that particular person.

Answer: B, C, D

Q2. Which of the following are classification problems?

• Predict the runs a cricketer will score in a particular match.
• Predict which team will win a tournament.
• Predict whether it will rain today.
• Predict your mood tomorrow.

Q3. Which of the following is a regression task?

• Predicting the monthly sales of a cloth store in rupees.
• Predicting if a user would like to listen to a newly released song or not based on historical data.
• Predicting the confirmation probability (in fraction) of your train ticket whose current status is waiting list based on historical data.
• Predicting if a patient has diabetes or not based on historical medical records.
• Predicting if a customer is satisfied or unsatisfied from the product purchased from an ecommerce website using the reviews he/she wrote for the purchased product.

Answer: A, C

Q4. Which of the following is an unsupervised learning task?

• Group audio files based on the language of the speakers.
• Group applicants to a university based on their nationality.
• Predict a student’s performance in the final exams.
• Predict the trajectory of a meteorite.

Answer: A, B

Q5. Which of the following is a categorical feature?

• Number of rooms in a hostel.
• Gender of a person.
• Your weekly expenditure in rupees.
• Ethnicity of a person.
• Area (in sq. centimeter) of your laptop screen.
• The color of the curtains in your room.
• Number of legs an animal has.
• Minimum RAM requirement (in GB) of a system to play a game like FIFA, DOTA.

Answer: B, D, F

Q6. Which of the following is a reinforcement learning task?

• Learning to drive a cycle
• Learning to predict stock prices
• Learning to play chess
• Learning to predict spam labels for e-mails

Q7. Let X and Y be a uniformly distributed random variable over the interval [0,4] and [0,6] respectively. If X and Y are independent events, then compute the probability, P(max(X,Y)>3)

• None of the above

Answer: 5/8

Q8. Find the mean of 0-1 loss for the given predictions:

Answer: 0.5

Q9. Which of the following statements are true? Check all that apply.

• A model with more parameters is more prone to overfitting and typically has higher variance.
• If a learning algorithm is suffering from high bias, only adding more training examples may not improve the test error significantly.
• When debugging learning algorithms, it is useful to plot a learning curve to understand if there is a high bias or high variance problem.
• If a neural network has much lower training error than test error, then adding more layers will help bring the test error down because we can fit the test set better.

Answer: A, B, C

Q10. Bias and variance are given by:

• E[f^(x)]−f(x),E[(E[f^(x)]−f^(x))2]
• E[f^(x)]−f(x),E[(E[f^(x)]−f^(x))]2
• (E[f^(x)]−f(x))2,E[(E[f^(x)]−f^(x))2]
• (E[f^(x)]−f(x))2,E[(E[f^(x)]−f^(x))]2

Answer: E[f^(x)]−f(x),E[(E[f^(x)]−f^(x))2]

Session: JAN-APR 2023

Q1) Which of the following is a supervised learning problem?

• Predicting rainfall based on historical data.
• Predicting if a customer is going to return or keep a particular product he/she purchased from e-commerce website based on the historical data about the customer purchases and the particular product.

Answer: b, c, d, e

Q2) Which of the following is not a classification problem?

• Predicting the temperature (in Celsius) of a room from other environmental features (such as atmospheric pressure, humidity, etc).
• Predicting if a cricket player is a batsman or bowler given his playing records.
• Predicting the price of a house (in INR) based on the data consisting prices of other houses (in INR) and its features such as area, number of rooms, location, etc.
• Filtering of spam messages.
• Predicting the weather for tomorrow as “hot,” “cold,” or “rainy” based on the historical data wind speed, humidity, temperature, and precipitation.

Answer: a, c

Q3) Which of the following is a regression task?

• Predicting the confirmation probability (in fraction) of your train ticket whose current status is the waiting list based on historical data.
• Predicting if a customer is satisfied or unsatisfied with the product purchased from an e-commerce website using the reviews he/she wrote for the purchased product.

Q4) Which of the following is an unsupervised task?

• Predicting if a new edible item is sweet or spicy based on the information of the ingredients, their quantities, and labels (sweet or spicy) for many other similar dishes.
• Grouping of hand-written digits from their image.
• Predicting the time (in days) a PhD student will take to complete his/her thesis to earn a degree based on the historical data such as qualifications, department, institute, research area, and time taken by other scholars to earn the degree.
• All of the above.

Answer: b, c

Q5) Which of the following is a categorical feature?

• Area (in sq. centimeters) of your laptop screen.

Answer: d, f

Q6) Let X and Y be a uniformly distributed random variable over the interval [0, 4] and [0, 6] respectively. If X and Y are independent events, then compute the probability, P(max(X,Y)>3)

Answer: f. 5/8

Q7) Let the trace and determinant of a matrix A[acbd] be 6 and 16 respectively. The eigenvalues of A are

• 3+i√7/2, 3−i√7/2, where i=√−1
• 3+i√7/4, 3−i√7/4, where i=√−1
• 3+i√7, 3−i√7, where i=√−1
• Can be computed only if A is a symmetric matrix.
• Cannot be computed as the entries of the matrix A are not given.

Answer: e. 3+i√7, 3−i√7, where i=√−1

Q8) What happens when your model complexity increases?

• Model Bias decreases
• Model Bias increases
• Variance of the model decreases
• Variance of the model increases

Answer: a, d

Q9) A new phone, E-Corp X1 has been announced and it is what you’ve been waiting for, all along. You decide to read the reviews before buying it. From past experiences, you’ve figured out that good reviews mean that the product is good 90% of the time and bad reviews mean that it is bad 70% of the time. Upon glancing through the reviews section, you find out that the X1 has been reviewed 1269 times and only 172 of them were bad reviews. What is the probability that, if you order the X1, it is a bad phone?

Answer: g. 0.181

Q10) Which of the following are false about bias and variance of overfitted and underfitted models?

• Underfitted models have high bias.
• Underfitted models have low bias.
• Overfitted models have low variance.
• Overfitted models have high variance.

Session: JUL-DEC 2022

1. Which of the following are supervised learning problems? (multiple may be correct)

• a. Learning to drive using a reward signal.
• b. Predicting disease from blood sample.
• c. Grouping students in the same class based on similar features.
• d. Face recognition to unlock your phone.

Answer: b, d

2. Which of the following are classification problems? (multiple may be correct)

• a. Predict the runs a cricketer will score in a particular match.
• b. Predict which team will win a tournament.
• c. Predict whether it will rain today.
• d. Predict your mood tomorrow.

3. Which of the following is a regression task? (multiple options may be correct)

• a. Predict the price of a house 10 years after it is constructed.
• b. Predict if a house will be standing 50 years after it is constructed.
• c. Predict the weight of food wasted in a restaurant during next month.
• d. Predict the sales of a new Apple product.

Answer: a, c, d

4. Which of the following is an unsupervised learning task? (multiple options may be correct)

• a. Group audio files based on language of the speakers.
• b. Group applicants to a university based on their nationality.
• c. Predict a student’s performance in the final exams.
• d. Predict the trajectory of a meteorite.

Answer: a, b

5. Given below is your dataset. You are using KNN regression with K=3. What is the prediction for a new input value (3, 2)?

Answer: 2.50

6. Which of the following is a reinforcement learning task? (multiple options may be correct)

Answer: a, b, c

7. Find the mean of squared error for the given predictions:

8. Find the mean of 0-1 loss for the given predictions:

9. Bias and variance are given by:

10. Which of the following are true about bias and variance? (multiple options may be correct)

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NPTEL Programming In Java Programming Assignment July-2024 Swayam

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Week 01 : Programming Assignment 1

Write a Java program to print the area and perimeter of a rectangle.

Week 01 : Programming Assignment 2

Write a Java program and compute the sum of an integer's digits.

Week 01 : Programming Assignment 3

Write a Java program to display n terms of natural numbers and their sum.

(Remember to match the output given exactly, including the spaces and new lines)

(passed with presentation error means you will get full marks)

Week 01 : Programming Assignment 4

Write a Java program to make such a pattern like a right angle triangle with the number increased by 1.

(Ignore presentation errors for this and all future programming assignments) (passed with presentation error means  you will get full marks )

Week 01 : Programming Assignment 5

Write a Java program to convert an integer number to a binary number.

Week 02 : Programming Assignment 1

Complete the code segment to call the method  display() of class Former first and then call display() method of class Latter.

Week 02 : Programming Assignment 2

Create a  class Student  with  private  attributes for  name  and  age .

Use a constructor to initialize these attributes and provide public getter methods to access them.

In the main method, an instance of Student is created and the student's details are printed.

Guideline to Solve:

§   Define the  Student class  with  private  attributes.

§   Use a constructor to initialize the attributes.

§   Implement getter methods for the attributes.

Follow the naming convetion used in the Fixed code.

Week 02 : Programming Assignment 3

Create a class  Rectangle  with attributes  length  and  width .

Provide two constructors: one with no parameters ( default to 1 ) and

another with parameters to initialize the attributes.

Use the  this  keyword to avoid name space collision.

Create a getArea() function that returns the area of the rectangle.

§   Define the  Rectangle  class with attributes and constructors.

§   Define a default Rectangle constructor that inializes length and width to 1.

§   Use the  this  keyword in the parameterized constructor.

§   Define a getArea() funtion that returns the area of there rectangle

Week 02 : Programming Assignment 4

Create a class  Circle  that encapsulates the properties of a circle.

The class should have a private field for the radius, a constructor to initialize the radius, and methods to calculate the area and circumference of the circle.

NOTE: use Math.PI for PI calculations (DO NOT USE 22/7)

§   Define the  Circle  class with attributes and constructors.

§   Define a getArea() funtion that returns the area of there Circle (use Math.PI)

§   Define a getCircumference() funtion that returns the circumference of there Circle (use Math.PI)

Week 02 : Programming Assignment 5

Complete the code by creating the constructor and the getter functions for a class Dog as defined below.

Week 03 : Programming Assignment 1

Create a class Department having a method  getCourses  that prints  "These are the department's courses" . It will have two subclasses , ComputerScience and MechanicalEngineering , each having a method with the same name that prints specific courses for the respective departments.Call the method by creating an object of each of the three classes.

Week 03 : Programming Assignment 2

Week 03 : programming assignment 3.

Write a program to print the factorial of a number by defining a recursive method named 'Factorial'.

Factorial of any number n is represented by n! and is equal to 1*2*3*....*(n-1)*n. E.g.-

4! = 1*2*3*4 = 24

3! = 3*2*1 = 6

2! = 2*1 = 2

Week 03 : Programming Assignment 4

Write a program to take integer inputs from user until he/she presses q ( Ask to press q to quit after every integer input ). Print average and product of all numbers.

Week 03 : Programming Assignment 5

Write a Java program to create a class called Employee with methods called work() and getSalary(). Create a subclass called HRManager that overrides the work() method and adds a new method called addEmployee().

Week 04 : Programming Assignment 1

Complete the code segment to swap two numbers using call by object reference.

Week 04 : Programming Assignment 2

1 - Problem Statement:        

Define a class  Point  with members

§   private double x;

§   private double y;

and methods:

§   public Point(double x, double y){}  // Constructor to create a new point?

§   public double slope(Point p2){} // Function to return the slope of the line formed from current Point and another Point (Assume that input will always be chosen so that slope will never be infinite)

Week 04 : Programming Assignment 3

This program to exercise the create static and non-static methods. A partial code is given, you have to define two methods, namely sum( ) and multiply( ). These methods have been called to find the sum and product of two numbers. Complete the code segment as instructed.  

Week 04 : Programming Assignment 4

The program in this assignment is attempted to print the following output:

-----------------OUTPUT-------------------

This is large

This is medium

This is small

This is extra-large

-------------------------------------------------

However, the code is intentionally with some bugs in it. Debug the code to execute the program successfully.

Week 04 : Programming Assignment 5

Consider First n even numbers starting from zero(0).Complete the code segment to calculate sum of  all the numbers divisible by 3 from 0 to n. Print the sum. Example:

Input: n = 5

Even number divisible by 3:0 6

Week 05 : Programming Assignment 1

Week 05 : Programming Assignment 2

Write a program to create an interface Searchable with a method search(String keyword) that searches for a given keyword in a text document. Create two classes Document and WebPage that implement the Searchable interface and provide their own implementations of the search() method.

Week 05 : Programming Assignment 3

Week 05 : programming assignment 4, week 05 : programming assignment 5, week 06 : programming assignment 1, week 06 : programming assignment 2, week 06 : programming assignment 3, week 06 : programming assignment 4, week 06 : programming assignment 5, week 07 : programming assignment 1, week 07 : programming assignment 2.

Write a program to print Swastika Pattern in Java. 

Input is 2 numbers. 

(Rows and Columns)

For Example:

   * *

NOTE: Do not print any spaces between the ‘*’

Output should match exactly as specified by the question

Week 07 : Programming Assignment 3

Write a program to remove all occurrences of an element from array in Java.

Week 07 : Programming Assignment 4

Write a p rogram to compute the sum of all prime numbers in a given range. The range value will be positive.

Follow the naming convention as given in the main method of the suffix code.

Week 07 : Programming Assignment 5

Code to create two threads, one printing even numbers and the other printing odd numbers.

§   The PrintNumbers class is declared, and it implements the Runnable interface. This interface is part of Java's concurrency support and is used to represent a task that can be executed concurrently by a thread.

§   Create a constructor of this class that takes two private instance variables (start and end) to represent the range of numbers that will be printed by the thread.

§   Create a run method that is required by the Runnable interface and contains the code that will be executed when the thread is started. In this case, it should prints odd numbers within the specified range (start to end) using a for loop.

§   Hint: Thread.currentThread().getName() returns the name of the currently executing thread, which is useful for identifying which thread is printing the numbers.

Week 08 : Programming Assignment 1

Complete the code segment to print the current year. Your code should compile successfully.

Note: In this program, you are not allowed to use any import statement. Use should use predefined class Calendar defined in java.util package.

Week 08 : Programming Assignment 2

Complete the code segment to call the default method in the interface First and Second.

Week 08 : Programming Assignment 3

Modify the code segment to print the following output.

-----------------OUTPUT------------------- (this line should not be printed)

Circle: This is Shape1

Circle: This is Shape2

-------------------------------------------------  (this line should not be printed) (Remember to match the output given exactly, including the spaces and new lines) (passed with presentation error means you will always get full marks)

Week 08 : Programming Assignment 4

Complete the code segment to execute the following program successfully. You should import the correct package(s) and/or class(s) to complete the code.

(Note: there is no error in the given fixed code, there is a way to print without using “System”)

(Hint: Use Static import)

Week 08 : Programming Assignment 5

In the following program, there may be multiple exceptions.

You have to complete the code using  ONLY ONE  try-catch block to handle all the possible exceptions.

For example, if user’s input is 1, then it will throw and catch “java.lang.NullPointerException“. (Hint: Try to catch the exception and print it) (NOTE: DO NOT USE MORE THAN ONE TRY CATCH, there may be a penalty if you use more than one try catch block)

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NPTEL Project Management Week 1 Assignment Answers

NPTEL Project Management Week 1 Assignment Answers:- In this post we have provided the answers to the Project Management Week 1

NPTEL Project Management Week 1 Assignment Answers 2022

Q1. You are the project manager for a high visibility project. The margin on this project is low, and it is extremely important that the cost estimates for the work on the project be accurate. While reviewing the cost estimates for this project you notice that one of the cost estimates for an element in the WBS is 10% higher than two previous projects for very similar work. What should you do?

Important Links:-

NPTEL Answers

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Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network…

amanchadha/coursera-deep-learning-specialization

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Deep learning specialization on coursera (offered by deeplearning.ai).

Programming assignments and quizzes from all courses in the Coursera Deep Learning specialization offered by deeplearning.ai .

Instructor: Andrew Ng

For detailed interview-ready notes on all courses in the Coursera Deep Learning specialization, refer www.aman.ai .

Run setup.sh to (i) download a pre-trained VGG-19 dataset and (ii) extract the zip'd pre-trained models and datasets that are needed for all the assignments.

This repo contains my work for this specialization. The code base, quiz questions and diagrams are taken from the Deep Learning Specialization on Coursera , unless specified otherwise.

2021 Version

This specialization was updated in April 2021 to include developments in deep learning and programming frameworks, with the biggest change being shifting from TensorFlow 1 to TensorFlow 2. This repo has been updated accordingly as well.

Programming Assignments

Course 1: neural networks and deep learning.

• Week 2 - PA 1 - Python Basics with Numpy
• Week 2 - PA 2 - Logistic Regression with a Neural Network mindset
• Week 3 - PA 3 - Planar data classification with one hidden layer
• Week 4 - PA 4 - Building your Deep Neural Network: Step by Step
• Week 4 - PA 5 - Deep Neural Network for Image Classification: Application

Course 2: Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

• Week 1 - PA 1 - Initialization
• Week 1 - PA 2 - Regularization
• Week 1 - PA 3 - Gradient Checking
• Week 2 - PA 4 - Optimization Methods
• Week 3 - PA 5 - TensorFlow Tutorial

Course 3: Structuring Machine Learning Projects

• There are no programming assignments for this course. But this course comes with very interesting case study quizzes (below).

Course 4: Convolutional Neural Networks

• Week 1 - PA 1 - Convolutional Model: step by step
• Week 1 - PA 2 - Convolutional Neural Networks: Application
• Week 2 - PA 1 - Keras - Tutorial - Happy House
• Week 2 - PA 2 - Residual Networks
• Week 2 - PA 2 - Transfer Learning with MobileNet
• Week 3 - PA 1 - Car detection with YOLO for Autonomous Driving
• Week 3 - PA 2 - Image Segmentation Unet
• Week 4 - PA 1 - Art Generation with Neural Style Transfer
• Week 4 - PA 2 - Face Recognition

Course 5: Sequence Models

• Week 1 - PA 1 - Building a Recurrent Neural Network - Step by Step
• Week 1 - PA 2 - Dinosaur Land -- Character-level Language Modeling
• Week 1 - PA 3 - Jazz improvisation with LSTM
• Week 2 - PA 1 - Word Vector Representation and Debiasing
• Week 2 - PA 2 - Emojify!
• Week 3 - PA 1 - Neural Machine Translation with Attention
• Week 3 - PA 2 - Trigger Word Detection
• Week 4 - PA 1 - Transformer Network
• Week 3 - PA 2 - Transformer Network Application: Named-Entity Recognition
• Week 3 - PA 2 - Transformer Network Application: Question Answering

Quiz Solutions

• Week 1 Quiz - Introduction to deep learning: Text | PDF
• Week 2 Quiz - Neural Network Basics: Text | PDF
• Week 3 Quiz - Shallow Neural Networks: Text | PDF
• Week 4 Quiz - Key concepts on Deep Neural Networks: Text | PDF
• Week 1 Quiz - Practical aspects of deep learning: Text | PDF
• Week 2 Quiz - Optimization algorithms: Text | PDF
• Week 3 Quiz - Hyperparameter tuning, Batch Normalization, Programming Frameworks: Text | PDF
• Week 1 Quiz - Bird recognition in the city of Peacetopia (case study): Text | PDF
• Week 2 Quiz - Autonomous driving (case study): Text | PDF
• Week 1 Quiz - The basics of ConvNets: Text | PDF
• Week 2 Quiz - Deep convolutional models: Text | PDF
• Week 3 Quiz - Detection algorithms: Text | PDF
• Week 4 Quiz - Special applications: Face recognition & Neural style transfer: Text | PDF
• Week 1 Quiz - Recurrent Neural Networks: Text | PDF
• Week 2 Quiz - Natural Language Processing & Word Embeddings: PDF
• Week 3 Quiz - Sequence models & Attention mechanism: Text | PDF

I recognize the time people spend on building intuition, understanding new concepts and debugging assignments. The solutions uploaded here are only for reference . They are meant to unblock you if you get stuck somewhere. Please do not copy any part of the code as-is (the programming assignments are fairly easy if you read the instructions carefully). Similarly, try out the quizzes yourself before you refer to the quiz solutions. This course is the most straight-forward deep learning course I have ever taken, with fabulous course content and structure. It's a treasure by the deeplearning.ai team.

Contributors 9

• Jupyter Notebook 98.6%

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Data Base Management System | Week 1

Session: JAN-APR 2024

Course Name: Data Base Management System

Course Link: Click Here

For answers or latest updates join our telegram channel: Click here to join

These are Data Base Management System Week 1 Assignment Answers

Q1. A relation R has 2 candidate keys with 1 attribute each. There are 6 possible super keys of R. What is the total number of attributes in R? a) 2 b) 3 c) 4 d) 5

Answer: b) 3

Q2. Consider the following instances of the relation: SEMESTER1 (Student, Marks) and SEMESTER2(Student, Marks) Which of the following Relational Algebra produces the Name and SEMESTER1 Marks of only those Students who did not appear in SEMESTER2? a) (II_Student (SEMESTER2) — II_Student (SEMESTER1)) >< SEMESTER1 b) (II_Student (SEMESTER2) — II_Student (SEMESTER1)) >< SEMESTER2 c) (II_Student (SEMESTER1) — II_Student (SEMESTER2)) >< SEMESTER2 d) (II_Student (SEMESTER1) — II_Student (SEMESTER2)) >< SEMESTER1

Answer: d) (II_Student (SEMESTER1) — II_Student (SEMESTER2)) >< SEMESTER1

Q3. Consider the following instance of the relation Counters(CNo, Item, Price, Category) Identify the valid primary key for the relation Counters(CNo, Item, Price, Category) from the given instance. a) {CNo, Item} b) {Item, Price} c) {Price, Category} d) {CNo, Item, Category}

Answer: b) {Item, Price}

Q4. Consider the following instance of the relation Seating(SNo, Preference, Coach, Name) Identifying the primary key from the given instance, select the tuple that can NOT be inserted to Seating. a) (11, WS, D1, Harsh S.) b) (2, NP, D2, Anukul K.) c) (6, NWS, D2, Raima H.) d) (6, NULL, NULL, NULL)

Answer: b) (2, NP, D2, Anukul K.)

Q5. Consider the following RA: II_track(ocategory=_’Pop’ (Music)) Which of the following statements is true? a) Displays the details of all Music from Pop Category b) Displays the details of at least one Music from Pop Category c) Displays at most one track from Pop Category d) Displays all the tracks from Pop Category

Answer: d) Displays all the tracks from Pop Category

Q6. Let R1 ( X ,Y) and R2( A ,B,C) be two relations in a schema. The primary keys are shown underlined. Let C be a foreign key in R2 referring to R2. Suppose, there is no violation of the above referential integrity constraint in the corresponding relation instances r1 and r2. Which one of the following relational algebra expressions would necessarily produce an empty relation? a) II_X(r1) —II_C(r2) b) II_C(r2) —II_X(r1) c) II_X(r1><r2) d) II_C(r1><r2)

Answer: b) II_C(r2) —II_X(r1)

Q7. Consider the following relations: Parts( PartID , Name, Price ). Supplier( SupID , Name, Location). Order(SupID, PartID, Quantity) . If SupID and PartID together are used to uniquely identify a row in Order table, which of the following option is correct for describing such key in Order table? a) Alternate key b) Composite key c) Compound key d) Surrogate key

Answer: c) Compound key

Q8. Consider the following table: Identify the correct operation(s) which produces the following output from the above relation. a) II_(Address=”Kolkata’) ^ _(Age>25)(StudentDetails) b) II_(Address=”Kolkata’) v _(Age>25)(StudentDetails) c) o-_(Address=”Kolkata’) ^ _(Age>25)(StudentDetails) d) o-_(Address=”Kolkata’) v _(Age>25)(StudentDetails)

Answer: d) o-_(Address=”Kolkata’) v _(Age>25)(StudentDetails)

Q9) Consider the following tables: Identify the correct operation(s) which will be produce the following output from the above two relations. a) (Student x Department) b) II_(StudName, Student.DeptName, Fees) (o-_Student.DeptName = Department.DeptName) (Student x Department) c) o-_(StudName, Student.DeptName, Fees)(Student >< Department) d) (Student >< Department)

Answer: b), d) b) II_(StudName, Student.DeptName, Fees) (o-_Student.DeptName = Department.DeptName) (Student x Department) d) (Student >< Department)

Q10. Which of the following can be a candidate key for the following instance? a) {StudName} b) {DeptName} c) {StudName, DeptName} d) {Address, Age}

Answer: c) {StudName, DeptName}

More Solutions of Data Base Management System: Click Here

More NPTEL Solutions: Click Here

Session: JAN-APR 2023

Q1) Which level of abstraction describes types of data that are stored in the Database? a) Physical level b) Logical level c) View level d) Abstraction level

Answer: a) Physical level

Q2) Identify the valid primary key for the relation paper_info from the given instance. a) paper_id b) paper_id, corresponding Author c) conference_id, corresponding_Author d) paper_id, conference_id

Answer: a) paper_id

Q3) Identify the correct statement/s. a) Project (pCode, pName) is an instance of a relation schema. b) Project (pCode, pName) is an example of a physical schema. c) (2245, HardFort) is an instance of a relation schema. d) (2245, HardFort) is an example of a logical schema.

Answer: a) Project (pCode, pName) is an instance of a relation schema.

Q4) Consider a relation Vehicle (VID, Model, Speed, Color) where the superkeys are as follows: {VID}, {VID, Model}, {Speed, Color}, {Speed, Color, Model}. Select the possible candidate key(s). a) {VID} b) {Speed} c) {Color} d) {Speed, Color}

Answer: a) {VID}

Q5) Consider the following relations: Book (ISBN, Title, Pages) BookGenre (ISBN, Genre) What does the following relational algebra expression represent? IIISBN((Pages>100 Book) (Genre-Fiction/BookGenre)) a) Find the ISBN of all Book with more than 100 Pages. b) Find the ISBN of all Book with more than 100 Pages or are of Genre ‘Fiction’. c) Find the ISBN of all Book with more than 100 Pages but are not of Genre ‘Fiction’. d) Find the ISBN of all Book with more than 100 Pages and are of Genre ‘Fiction’.

Answer: d) Find the ISBN of all Book with more than 100 Pages and are of Genre ‘Fiction’.

Q6) Consider the following relational schema: ImageCode (ImageID, Name) ImageBook (BookID, Image ID, Page) What will be the Relational Algebra equivalent to the following statement? “Find the names of all Images on Page 100.” a) Name (ImageCode Page=100 (ImageBook)) X b) Name (Ipage=100 (ImageCode) ImageBook) c) IIName(IIpage=100 (ImageCode) ▷ ImageBook) d) IIName (Image Code Page=100 (ImageBook))

Answer: d) IIName (Image Code Page=100 (ImageBook))

Q7) Consider the following tables: Which of the following operations will return S1 itself? a) S2-(S2-S1) b) S1-(S2-S1) c) S1-(S1-S2) d) S2-(S1-S2)

Answer: c) S1-(S1-S2)

Q8) Consider the following tables: Identify the correct operation(s) which will be produce the following output from the above relations. a) (#Faculties>=20000) (UniversitiesDetails) b) (#Faculties>20000) (Universities Details) c) IIStateName, #State Universities, #Faculties (#Faculties>=20000) (Universities Details) d) IlStateName, #State Universities, #Faculties (#Faculties> 20000) (UniversitiesDetails)

Answer: c) IIStateName, #State Universities, #Faculties (#Faculties>=20000) (Universities Details)

Q9) Consider the following tables: Identify the correct operation(s) which will be produce the following output from the above two relations. a) Details Details2 b) Details – Details₁ c) (Details₁ U Details ₂) n (Details₁ Details₂) d) (Details1 Details2) U (Details2 – Details 1)

Answer: d) (Details1 Details2) U (Details2 – Details 1)

Q10) Which of the following can be a candidate key for the following instance? a) {StateName} b) {#State Universities} c) {#Faculties} d) {StateName, #Central Universities, #State Universities}

Answer: a) {StateName}