NPTEL Deep Learning Week 3 Assignment Answers 2023

NPTEL Deep Learning Assignment 1 Solutions 2023

NPTEL Deep Learning Week 3 Assignment Answers 2023

Table of Contents:-

1. What is the shape of the loss landscape during optimization of SVM? a. Linear b. Paraboloi d c. Ellipsoidal d. Non-convex with multiple possible local minimum

2. For a 2-class problem what is the minimum p o ssible number of support vectors. Assume there are more than 4 examples from each class a. 4 b. 1 c. 2 d. 8

3. Choose the correct option regarding classification using SVM for two classes Statement i: While designing an SVM for two c lasses, the equation y (a*x; + b) ≥ 1 is used to choose the separating plane using the training vectors. Statement ii: During inference, for an unknown vector x;, if y;(ax; + b) ≥ 0, then the vector can be assigned class 1. Statement iii : During inference, for an unknown vector x;, if (ax; + b) > 0, then the vector can be assigned class 1. a. Only Statement i is true b. Both Statements i a nd it are true c. Both Statements i and i are true d. Both Statements ii and ili are true

4. Find the scalar projection of vector b = <-4 , 1 > onto vector a = <1,2>?

NPTEL Deep Learning Week 3 Assignment Answers 2023

6. Suppose we have the below set of points with their respective c lasses as shown in the table. Answer the following question based on the table.

NPTEL Deep Learning Week 3 Assignment Answers 2023

7. Suppose we have the below set of points with their respective classes as shown in the table. Answer the following question based on the table.

NPTEL Deep Learning Week 3 Assignment Answers 2023

8. Suppose we have the below set of points with their respective classes as shown in the table. Answer the following question based on the table.

NPTEL Deep Learning Week 3 Assignment Answers 2023

9. Suppose we have the below set of points with their respective classes as shown in the table. Answer the following question based on the table.

NPTEL Deep Learning Week 3 Assignment Answers 2023

10. Which one of the following is a valid representation of hinge loss (of margin = 1) for a two-class problem? y = class label (+1 or -1). p = predicted (not normalized to denote any probability) value for a class.? a. L(y, p) = max(0, 1 – yp) b. L(y, p) = min( 0 , 1 – yp) c. L(y, p) = max(0, 1 + yp) d. None of the above

NPTEL Deep Learning Week 2 Assignment Answers 2023

1. Choose the correct option regarding discriminant functions g(x) for multiclass classification (x is the feature vector to be classified) Statement i : Risk value R a; x) in Bayes minimum risk cla s sifier can be used as a discriminant function. Statement ii: Negative of Risk value R (at|×) in Bayes minimum risk classifier can be used as a discriminant function. Statement iii: Aposteriori probability P(w; x) in Bayes minimum error classifier can be used as a discriminant function. Statement iv : Negative of Aposteriori probability P(w; x) in Bayes minimum error classifier can be used as a discriminant function. a. Only Statement i is true b. Both Statements ii and ili are true c. Both Statements i and iv are true d. Both Statements i and iv are true

2. Which of the fo ll owing is regarding functions of discriminant functions gi(x) i.e., f(g(x)) a. We can not use functions of discriminant functions f(g(x)), as discriminant functions for multiclass classification. b. We can use functions of discriminant functions, f(g(x)), as discriminant functions for multiclass classification provided, they are constant functions i.e., f(g(x)) = C where C is a constant. c. We can use functions of discriminant functions, f(g(x)), as discriminant functions for multiclass classification provided, they are monotonically increasing functions. d. None of the above is true.

3. The class conditional probability density function for the class w i ; i.e., P(x| w i ) for a multivariate normal (or Gaussian) distribution (where x is a d dimensional feature vector) is given by

NPTEL Deep Learning Week 3 Assignment Answers 2023

4. There are some data points for two different classes given below. Class 1 points: {(2, 6), (3, 4), (3, 8), (4, 6)} Class 2 points: {(3, 0), (1, -2), (5, – 2 ), (3, -4)} Compute the mean vectors μ 1 and μ 2 for these two classes and choose the correct option.

a. μ 1 = [2 6] and μ 2 = [3 -1] b. μ 1 = [3 6] and μ 2 = [2 -2] c. μ 1 = [3 6] and μ 2 = [3 -2] d. μ 1 = [3 5] and μ 2 = [2 -3]

5. There are some data points for two different classes given below. Class 1 points: {(2, 6), (3, 4), (3, 8), (4, 6)} Class 2 points: {(3, 0), (1, -2), (5, -2), (3, -4)} Compute the covariance matrices Σ1 and Σ2 and choose the correct option.

NPTEL Deep Learning Week 3 Assignment Answers 2023

6. There are some data points for two different classes given below. Class 1 points: {(2, 6), (3, 4), (3, 8), (4, 6)} Class 2 points: {(3, 0), (1, -2), (5, -2), (3, -4)}

NPTEL Deep Learning Week 3 Assignment Answers 2023

7. Let  ∑ i ; represents the covariance matrix for i t h class. Assume that the classes have the same co-variance matrix. Also assume that the features are statistically independent and have same co-variance. Which of the following is true? a. ∑ i ; = ∑, (diagonal elements of ∑ are zero) b. ∑ i ; = ∑, (diagonal elements of 2 are non-zero and different from each other, rest of the elements are zero) C. ∑ i ; =∑, (diagonal elements of 2 are non-zero and equal to each other, rest of the elements are zero) d. None of these

8. The decision surface between two normally distributed class w1 and w2 is shown on the figure. Can you comment which of the following is true?

NPTEL Deep Learning Week 3 Assignment Answers 2023

10. You are g i ven some data points for two different class. Class 1 points: {(11, 11 ) , (13, 11), (8, 10), (9, 9), (7, 7), (7, 5), (15, 3)} Class 2 points: {(7, 11), (15, 9), (15, 7), (13, 5), (14, 4), (9, 3), (11, 3)} Assume that the points are samples from normal distribution and a two class Bayesian classifier is used to classify them. Also assume the prior probability of the classes are equal i.e., P(w1) =P(wz) Which of the following is true about the corresponding decision boundary used in the classifier? (Choose correct option regarding the given statements) Statement i: Decision boundary passes through the midpo i nt of the line segment joining the means of two classes Statement ii: Decision boundary will be orthogonal bisector of the line joining the means of two classes.

a. Only Statement i is true b. Only Statement ii is true c. Both Statement i and i are t r ue d. None of the statements are true

NPTEL Deep Learning Week 1 Assignment Answers 2023

1. Signature descriptor of an unknown shape is given in the figure, can y ou identify the unknown shape?

NPTEL Deep Learning Week 3 Assignment Answers 2023

  • c. Straight line
  • d. Rectangle

2. Signature descriptor of an unknown shape is given in the f i gure, If d (0) i s measured in cm., what is the area of the unknown shape?

  • a. 120 sq. cm.
  • c. 240 sq. cm.
  • d. 100 sq. cm.
  • b. 144 sq. cm.

3. To measure the Smoothness, coarseness and r e gularity of a region we use which of the transformation to extract feature?

  • Gabor Transformation
  • Wavelet Transformation
  • Both Ga b or, and Wavelet Transformation.
  • None of the Above.

4. Given the 5 x 5 image I (fig 1), we can compute the gray co-occurrence matrix C (fig 2) by specifying the displacement vector d = (dx, dy). Let the position operator be specified as (1, 1), which has the interpretation: one pixel to the right and one pixel below. (Both the image and the partial gray co-occurrence is given in the figure 1, and 2 respectively. Blank values and ‘x’ value in gray co-occurrence matrix are unknown.)

NPTEL Deep Learning Week 3 Assignment Answers 2023

What is the value of ‘x’?

5. Given the 5 x 5 image I (fig 1), we can compute the gray co-occurrence m a trix by specifying the displacement vector d = (dx, dy). Let the position operator be specified as (1, 1), which has the interpretation: one pixel to the right and one pixel below. What is the value of maximum probability descriptor?

6. Which of the following is a region descriptor?

  • a. Polygonal Representation
  • b. Fourier descriptor
  • c. Signature
  • d. Intensity histogram.

7. We use gray co-occurrence matrix to extract whic h type of information?

  • a. Boundary
  • d. Zero Crossing rate.

8. A single card is drawn f rom a standard deck of playing cards. What is the probability of that a heart is drawn or a 5? (Hints: A standard deck of 52 cards has 4 suits namely heart, spades, diamonds and clubs)

9. which of following is strictly true for a two-class problem Bayes minimum error classifier? (The two different classes are w1 and w2, and input feature vector is x)

  • a. Choose w1 if P(x/wi) > P(x/w2)
  • b. Choose w1 if P(w1)>P(w2)
  • c. Choose w2 if P(w1/x)>P(w2/x)
  • d. Choose w1 if P(w1/x)>P(w2/x)

10. Consider two class Bayes’ Minimum Risk Classifier. Probability of c l asses W1 and W2 are, P (w1) =0.2 and P (w2) =0.8 respectively. P (x| w1) = 0.75, P (x| w2) = 0.5 and the loss matrix values are

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Deep Learning | NPTEL 2023 | Week 1 Assignment 1 solutions

This set of MCQ(multiple choice questions) focuses on the Deep Learning NPTEL 2023 Week 1 Assignment 1 Solutions .

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Week 1 : Assignment Answers Week 2: Assignment Answers Week 3: Assignment Answers Week 4: Assignment Answers Week 5: Assignment Answers Week 6: Assignment Answers Week 7: Assignment Answers Week 8: Assignment Answers Week 9: Assignment Answers Week 10: Assignment Answers Week 11: Assignment Answers Week 12: Assignment Answers

NOTE:  You can check your answer immediately by clicking show answer button. Deep Learning NPTEL 2023 Week 1 Assignment 1 Solutions” contains 10 questions.

Now, start attempting the quiz.

Deep Learning NPTEL 2023 Week 1 Quiz Solutions

Q1. From a pack of 52 cards, two cards are drawn together at random. What is the probability of both the cards being kings?

a) 1/15 b) 25.57 c) 35/256 d) 1/221

Answer: d) 1/221

Q2. For a two class problem Bayes minimum error classifier follows which of following rule? (The two different classes are ω 1 and ω 2, and input feature vector is x)

a) Choose ω 1 if P( ω 1/x) > P( ω 2/x) b) Choose ω 1 if P( ω 1) > P( ω 2) c) Choose ω 2 if P( ω 1) < P( ω 2) d) Choose ω 2 if P( ω 1/x) > P( ω 2/x)

Answer: a) Choose ω1 if P(ω1/x) > P(ω2/x)

Q3. The texture of the region provides measure of which of the following properties?

a) Smoothness alone b) Coarseness alone c) Regularity alone d) Smoothness, coarseness and regularity

Answer: d) Smoothness, coarseness and regularity

Deep Learning NPTEL 2023 week 1 Assignment Solutions

Q4. Why convolution neural network is taking off quickly in recent times? (Check the options that are true.)

a) Access to large amount of digitized data b) Integration of feature extraction within the training process c) Availability of more computational power d) All of the above

Answer: d) All of the above

Q5. The bayes formula states:

a) posterior = likelihood*prior / evidence b) posterior = likelihood*evidence / prior c) posterior = likelihood * prior d) posterior = likelihood * evidence

Answer: c) posterior = likelihood * prior

Q6. Suppose Fourier descriptor of a shape has K coefficient, and we remove last few coefficient and use only m (m<k) number of coefficient to reconstruct the shape. What will be effect of using truncated Fourier descriptor on the reconstructed shape?

a) We will get a smoothed boundary version of the shape b) We will get only the fine details of the boundary of the shape c) Full shape will be reconstructed without any loss of information d) Low frequency component of the boundary will be removed from contour of the shape

Answer: a) We will get a smoothed boundary version of the shape

Deep Learning NPTEL week 1 Assignment Solutions

Q7. The plot of distance of the different boundary point from the centroid of the shape taken at various direction is known as

a) Signature descriptor b) Polygonal descriptor c) Fourier descriptor d) Convex Hull

Answer: a) Signature descriptor

Q8. If the larger value of gray co-occurrence matrix are concentrated around the main diagonal, then which one of the following will be true?

a) The value of element difference moment will be high b) The value of inverse element difference moment will be high c) The value of entropy will be very low d) None of the above

Answer: d) None of the above

Q9. Which of the following is a Co-occurrence matrix based descriptor

a) Entropy b) Uniformity c) Signature d) Inverse Element difference moment e) All of the above

Answer: d) Inverse Element difference moment

Q10. Consider two class Bayes’ Minimum Risk Classifier. Find the Risk R (a2 | x)

a) 0.42 b) 0.61 c) 0.48 d) 0.39

Answer: b) 0.61

Q1. Pick out the appropriate shape of decision boundary if the number of inputs is three.

a) Point b) Line c) Plane d) Hyperplane

Answer: c) Plane

Q2. Pick out the one in biological neuron that is responsible for receiving signal from other neurons.

a) Dendrite b) Synapse c) Soma d) Axon

Answer: a) Dendrite

Q3. Which of the following is considered as a drawback of Deep Learning?

a) Numerical stability b) Overfitting never occurs c) Sharp minima d) Overfitting always occurs

Answer: c) Sharp minima

Q4. Neurons play a vital role in how humans respond to the outside world. When does this occur?

a) Any one neuron gets activated b) All the neurons of massively parallel interconnected network of neurons are activated. c) Specific set of these neurons fire and relay the information to other neurons d) At least 10% of the total number of neurons in the brain

Answer: c) Specific set of these neurons fire and relay the information to other neurons

Q5. Consider a Mc Culloch Pitts Neuron for which the inputs are x1,x2 and x3. Also, the aggregate function g(x) is an OR function. What is the thresholding parameter for the same?

a) 0 b) 1 c) 2 d) 3

Answer: b) 1

Q6. Which of the following statements are True? Statement I. Mc. Culloch Pitts neuron can be used to represent any boolean function Statement II. If any of the inputs in a Mc. Culloch Pitts Neuron is inhibitory, then output will be zero

a) Only I b) Only II c) Both d) None

Answer: b) Only II

Q7. Pick out the boolean function that is not linearly separable.

a) AND b) OR c) NOR d) XOR

Answer: d) XOR

Q8. In a perceptron learning algorithm, what is the initial value of the weights before the algorithm starts learning?

a) All weights set to zero b) All weights set to one c) All weights assigned random values d) All weights assigned values specific to the application in hand

Answer: c) All weights assigned random values

Q9. What is the condition for convergence of a perceptron learning algorithm?

a) Always converges b) Data is linearly separable c) Data is linearly non-separable d) May or may not converge depending on the data

Answer: b) Data is linearly separable

Q10. Select all the statements that hold TRUE for a Single Perceptron.

a) Inputs are weighted b) Threshold is hand coded c) Only Real inputs are allowed d) Both Real and boolean inputs are allowed e) Can solve only linearly separable data

Answer: a), d), e)

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deep learning nptel assignment 8 solutions 2023

mode of Study

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Advances in Strategic Human Resource Management

Advances in Strategic Human Resource Management (HRM)

The Advances in Strategic Human Resource Management (HRM) certification course is a 4-week online programme that offers an in-depth exploration of strategies and methodologies within the landscape of human resource management. Students are provided with the knowledge and skills necessary to drive organisational success through the Advances in Strategic Human Resource Management (HRM) Certification by NPTEL .

The online course provides students the effective strategies for creating employee engagement and organisational culture. The Advances in Strategic Human Resource Management (HRM) training explores emerging trends such as digital HR technologies, diversity and inclusion initiatives, and the integration of HRM with overall business strategy.

Also Read:  Online Human Resource Management Certification Courses

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About nptel.

In the digital age, technology has become an integral part of education, transforming traditional learning methods and opening up new avenues for knowledge dissemination. One such pioneering initiative in India is the National Programme on Technology Enhanced Learning (NPTEL), a collaborative effort by the Indian Institutes of Technology (IITs) and the Indian Institute of Science (IISc). NPTEL has emerged as a game-changer in the realm of higher education, offering high-quality learning resources to millions of students across the country. NPTEL offers a diverse range of courses covering various branches of engineering, science, humanities, and management. These courses are developed and delivered by faculty members from the IITs and IISc, renowned for their expertise in their respective fields. The content includes video lectures, lecture notes, assignments, quizzes, and discussion forums, providing learners with a comprehensive learning experience. Since its inception, NPTEL has made significant strides in revolutionizing education in India. With millions of registered users and a vast repository of courses, it has emerged as one of the largest online learning platforms in the country. Its impact extends beyond the boundaries of academia, empowering students, educators, and professionals alike to upskill, reskill, and stay abreast of the latest developments in their respective fields. Furthermore, NPTEL's influence has transcended national borders, with learners from around the world benefiting from its rich educational resources. Its global outreach reflects the growing demand for quality online education and underscores India's leadership in the field of technology-enhanced learning.

deep learning nptel assignment 8 solutions 2023

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nptel-solutions

Here are 59 public repositories matching this topic..., kishanrajput23 / nptel-the-joy-of-computing-using-python.

Study materials related to this course.

  • Updated Oct 27, 2023

kishanrajput23 / NPTEL-Programming-In-java

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omunite215 / NPTEL-Programming-in-Java-Ultimate-Guide

I am sharing my journey of studying a course on Programming in Java taught by Prof.Debasis Samanta Sir IIT Kharagpur

  • Updated Dec 4, 2023

kadeep47 / NPTEL-Getting-Started-With-Competitive-Programming

[Aug - Oct 2023] Solutions for NPTEL Course Getting started with competitive programming weekly assignment.

  • Updated Sep 6, 2023

Md-Awaf / NPTEL-Course-Getting-started-with-Competitive-Programming

Solutions for NPTEL Course Getting started with competitive programming weekly assignment.

  • Updated Apr 20, 2023

rvutd / NPTEL-Joy-of-Computing-2020

Programming Assignment Solutions

  • Updated May 5, 2020

guru-shreyansh / NPTEL-Programming-in-Java

The sole intention behind this repository is to help the beginners in Java with the course contents.

  • Updated Aug 1, 2021

gunjanmimo / NPTEL-The-Joy-of-Computing-using-Python

  • Updated Jan 26, 2020

avinashyadav16 / The-Joy-of-Computing-Using-Pyhton

12 Weeks long NPTEL Elective MOOC Course's codes, assignments and solutions.

  • Updated Oct 30, 2023
  • Jupyter Notebook

AdishiSood / The-Joy-of-Computing-using-Python

  • Updated Apr 28, 2021

gxuxhxm / NPTEL-The-Joy-of-Computing-using-Python

NPTEL-The-Joy-of-Computing-using-Python with NOTES and Weekly quizes Answers

  • Updated Dec 31, 2023

NPTEL-Course / Programming-Data-Structures-And-Algorithms-Using-Python

Nptel Course Solutions : Programming, Data Structures And Algorithms Using Python

  • Updated Nov 30, 2020

tdishant / NPTEL-Joy-of-Computing-Using-Python

Python code from week-3 to week-12 for the NPTEL course The Joy of Computing using Python

  • Updated Oct 26, 2021

TarunSehgal27 / NPTEL-JAVA-2020

this is a repo about the java program headed by Debasis Samantha during 2020

  • Updated Apr 23, 2020

NPTEL-Course / Google-Cloud-Computing-Foundations

Nptel Course Solution : Google Cloud Computing Foundations

  • Updated Nov 19, 2020

Anmol-PROgrammar / SWAYAM-Programming_In_Java-NPTEL

This site contains the weekly( i.e. 1-9) questions and their solution of NPTEL-SWAYAM course "Programming in Java".

  • Updated Aug 19, 2021

lonebots / python-programming-joc-nptel

Python programming repository for NPTEL joy of computing course

  • Updated Dec 21, 2020

CGreenP / NPTEL-Introduction-to-Programming-in-C-Assignment-4-Question-3

NPTEL Introduction to Programming in C Assignment 4 Question 3

  • Updated Apr 7, 2024

CGreenP / NPTEL-Introduction-to-Programming-in-C-Assignment-4-Question-1

NPTEL Introduction to Programming in C Assignment 4 Question 1

  • Updated Apr 2, 2024

CGreenP / NPTEL-Introduction-to-Programming-in-C-Assignment-2-Question-2

NPTEL Introduction to Programming in C Assignment 2 Question 2

  • Updated Mar 21, 2024

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Rusmania

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Out of the Centre

Savvino-storozhevsky monastery and museum.

Savvino-Storozhevsky Monastery and Museum

Zvenigorod's most famous sight is the Savvino-Storozhevsky Monastery, which was founded in 1398 by the monk Savva from the Troitse-Sergieva Lavra, at the invitation and with the support of Prince Yury Dmitrievich of Zvenigorod. Savva was later canonised as St Sabbas (Savva) of Storozhev. The monastery late flourished under the reign of Tsar Alexis, who chose the monastery as his family church and often went on pilgrimage there and made lots of donations to it. Most of the monastery’s buildings date from this time. The monastery is heavily fortified with thick walls and six towers, the most impressive of which is the Krasny Tower which also serves as the eastern entrance. The monastery was closed in 1918 and only reopened in 1995. In 1998 Patriarch Alexius II took part in a service to return the relics of St Sabbas to the monastery. Today the monastery has the status of a stauropegic monastery, which is second in status to a lavra. In addition to being a working monastery, it also holds the Zvenigorod Historical, Architectural and Art Museum.

Belfry and Neighbouring Churches

deep learning nptel assignment 8 solutions 2023

Located near the main entrance is the monastery's belfry which is perhaps the calling card of the monastery due to its uniqueness. It was built in the 1650s and the St Sergius of Radonezh’s Church was opened on the middle tier in the mid-17th century, although it was originally dedicated to the Trinity. The belfry's 35-tonne Great Bladgovestny Bell fell in 1941 and was only restored and returned in 2003. Attached to the belfry is a large refectory and the Transfiguration Church, both of which were built on the orders of Tsar Alexis in the 1650s.  

deep learning nptel assignment 8 solutions 2023

To the left of the belfry is another, smaller, refectory which is attached to the Trinity Gate-Church, which was also constructed in the 1650s on the orders of Tsar Alexis who made it his own family church. The church is elaborately decorated with colourful trims and underneath the archway is a beautiful 19th century fresco.

Nativity of Virgin Mary Cathedral

deep learning nptel assignment 8 solutions 2023

The Nativity of Virgin Mary Cathedral is the oldest building in the monastery and among the oldest buildings in the Moscow Region. It was built between 1404 and 1405 during the lifetime of St Sabbas and using the funds of Prince Yury of Zvenigorod. The white-stone cathedral is a standard four-pillar design with a single golden dome. After the death of St Sabbas he was interred in the cathedral and a new altar dedicated to him was added.

deep learning nptel assignment 8 solutions 2023

Under the reign of Tsar Alexis the cathedral was decorated with frescoes by Stepan Ryazanets, some of which remain today. Tsar Alexis also presented the cathedral with a five-tier iconostasis, the top row of icons have been preserved.

Tsaritsa's Chambers

deep learning nptel assignment 8 solutions 2023

The Nativity of Virgin Mary Cathedral is located between the Tsaritsa's Chambers of the left and the Palace of Tsar Alexis on the right. The Tsaritsa's Chambers were built in the mid-17th century for the wife of Tsar Alexey - Tsaritsa Maria Ilinichna Miloskavskaya. The design of the building is influenced by the ancient Russian architectural style. Is prettier than the Tsar's chambers opposite, being red in colour with elaborately decorated window frames and entrance.

deep learning nptel assignment 8 solutions 2023

At present the Tsaritsa's Chambers houses the Zvenigorod Historical, Architectural and Art Museum. Among its displays is an accurate recreation of the interior of a noble lady's chambers including furniture, decorations and a decorated tiled oven, and an exhibition on the history of Zvenigorod and the monastery.

Palace of Tsar Alexis

deep learning nptel assignment 8 solutions 2023

The Palace of Tsar Alexis was built in the 1650s and is now one of the best surviving examples of non-religious architecture of that era. It was built especially for Tsar Alexis who often visited the monastery on religious pilgrimages. Its most striking feature is its pretty row of nine chimney spouts which resemble towers.

deep learning nptel assignment 8 solutions 2023

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635th Anti-Aircraft Missile Regiment

635-й зенитно-ракетный полк

Military Unit: 86646

Activated 1953 in Stepanshchino, Moscow Oblast - initially as the 1945th Anti-Aircraft Artillery Regiment for Special Use and from 1955 as the 635th Anti-Aircraft Missile Regiment for Special Use.

1953 to 1984 equipped with 60 S-25 (SA-1) launchers:

  • Launch area: 55 15 43N, 38 32 13E (US designation: Moscow SAM site E14-1)
  • Support area: 55 16 50N, 38 32 28E
  • Guidance area: 55 16 31N, 38 30 38E

1984 converted to the S-300PT (SA-10) with three independent battalions:

  • 1st independent Anti-Aircraft Missile Battalion (Bessonovo, Moscow Oblast) - 55 09 34N, 38 22 26E
  • 2nd independent Anti-Aircraft Missile Battalion and HQ (Stepanshchino, Moscow Oblast) - 55 15 31N, 38 32 23E
  • 3rd independent Anti-Aircraft Missile Battalion (Shcherbovo, Moscow Oblast) - 55 22 32N, 38 43 33E

Disbanded 1.5.98.

Subordination:

  • 1st Special Air Defence Corps , 1953 - 1.6.88
  • 86th Air Defence Division , 1.6.88 - 1.10.94
  • 86th Air Defence Brigade , 1.10.94 - 1.10.95
  • 86th Air Defence Division , 1.10.95 - 1.5.98

deep learning nptel assignment 8 solutions 2023

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NBA mock draft: Hawks soar for Sarr in post-lottery landscape

Depending on who you ask, the draft lottery format can either amount to a surprising blessing or a fateful stroke of bad fortune.

For the Atlanta Hawks - who had only a 3% chance at securing the No. 1 pick - Monday's 2024 NBA Draft Lottery offered an unlikely opportunity. For the Detroit Pistons - who, despite finishing with the league's worst record for a third successive season, again missed out on top billing - it was anything but.

With the order of the 14 lottery picks and the remaining field now established ahead of the two-day draft scheduled to start on June 26, here's a look at how things could shake out in consideration of team-specific needs:

Atlanta's Trae Young-led core has clearly plateaued in recent years, and the backcourt pairing with Dejounte Murray failed miserably. Though Young is an offensive dynamo with deep range and elite passing skills, his lack of size defensively puts the rest of the team at a disadvantage. That's where Sarr comes in.

Sarr has the rare combination of elite length (7-foot-1 with a 7-foot-4 wingspan) and above-average mobility for a center. Sarr's ability to clean up for Young's defensive mistakes as a rim-protector while also being able to handle switches onto smaller ball-handlers allows for more versatility on that end than with Clint Capela. If Sarr's perimeter jumper continues to grow, he could serve a role similar to Jaren Jackson Jr. on the Memphis Grizzlies as the perfect complement to a high-usage point guard.

One pick won't fill all of the holes on the Wizards' roster, but taking Clingan would address multiple needs. Washington had the third-worst defensive efficiency and allowed the most points in the paint per contest last season. The UConn product was among the top rim-protectors in college basketball, ranking sixth in the NCAA in block percentage (11.4%) and eighth in swats (2.5 per contest).

Clingan alters shots around the basket with his size and 7-foot-7 wingspan. The 7-foot-2 center should thrive in drop coverage as he frequently showed great mobility when switched onto guards. With Marvin Bagley currently penciled in as the starting center, the Wizards could certainly use an upgrade and long-term solution in the middle.

Risacher may earn consideration for the No. 1 overall pick. The 6-foot-10 forward is one of the youngest players in this year's draft class and has the potential to be an effective two-way presence. He's got the mobility and length to defend guards and wings, good ball-handling skills for his size, playmaking chops, and continues to improve his outside stroke.

Houston is playing with house money, having acquired this pick from the Brooklyn Nets as part of the James Harden trade. The Rockets' front office could opt for a more NBA-ready prospect, but it's unlikely they'll be selecting this high next year. Rolling the dice on Risacher's upside could pay off in the long run.

Coming off a freshman season in which he led all of college basketball shooting a ridiculous 52.1% from 3-point range on 144 attempts, Sheppard is tailor-made to provide much-needed gravity around rising superstar Victor Wembanyama on the offensive end. With the Spurs finishing third-last league-wide in percentage from distance, Sheppard immediately fills a need.

Sheppard would have made a real push for the No. 1 pick if he wasn't just 6-foot-2 with a 6-foot-3 wingspan. But with the biggest player in the league in Wembanyama roaming defensively, the Spurs are the team best positioned to hide Sheppard's lack of size while benefiting greatly from his strengths. Plus, with his improving point-guard skills, great defensive instincts, and combine-best vertical leap, Sheppard's role could grow beyond elite spot-up shooter.

Buzelis hurt his draft stock this season with an inefficient campaign on an overmatched G League Ignite team, but his blend of elite size on the wing with his offensive upside still projects him as one of the better prospects in the class.

After such a dreadful season, the Pistons may feel pressure to take a more surefire contributor on the wing, especially given Ausar Thompson still needs some seasoning to reach his expected potential. A forward duo of Thompson and Buzelis would be two players who shot under 30% from deep at their respective levels last season. But for a team desperate to climb out of the basement, taking a skilled combo forward could be their best chance at a ticket up the standings.

While Castle filled in nicely as the fifth option on the back-to-back national champions, he arguably has the highest ceiling among UConn's starting five. The 6-foot-6 guard provided a glimpse of his all-around package in the Huskies' Final Four win over Alabama, posting up smaller guards, creating for his teammates, and playing suffocating defense on Crimson Tide star Mark Sears.

Charlotte could use a secondary ball-handler alongside LaMelo Ball who can facilitate the offense when the former All-Star sits. The Hornets finished 25th and 28th in assists and offensive efficiency, respectively, last season and would greatly benefit from Castle's versatile skill set.

The Blazers have their long-term backcourt figured out, but everything else remains a big question mark. Portland's front office values youth and athleticism in the draft, and the 18-year-old Holland checks both boxes as well as anyone in the field. He's more of a tweener forward at just 6-foot-6 but plays much bigger with long arms.

Holland's jumper is the major swing skill here. If he continues to shoot 24% from three, he'll be an energy defender who's able to run the break in transition and wreak havoc in the dunker spot. If the jumper comes around, he projects as a player in the Jaylen Brown mold with his rugged style and nose for the basketball, along with solid rebounding and passing chops.

The Spurs could target Topic with the No. 4 pick, but if they choose the better shooter in Sheppard, the Serbian could fall in their laps with their second pick, given teams picking Nos. 5-7 have their respective point guards of the future already on the roster. Topic is a massive lead guard at 6-foot-6 who sees the floor well and plays under control.

Topic is a master in the pick-and-roll and, given the Spurs' lack of a true floor general, could create a whole new dynamic for Wembanyama's game. Like Sheppard, Topic has questions defensively, but his size will allow him to guard up positions, and the pair could see minutes together in offensive-minded lineups.

It wouldn't be a surprise if Memphis deals this pick for a more established veteran. However, in the event the Grizzlies keep the selection, they'll almost certainly be seeking a player who can help them win now. Knecht is a three-level scorer who could immediately inject life into the Grizzlies' offense.

Few players displayed better shot-making than the 6-foot-6 guard did last season. The Tennessee standout is a pull-up threat who can shoot off the dribble and make baskets coming off movement. He had eight 30-point performances during the 2023-24 campaign, including a 40-point explosion versus Kentucky. Knecht made 38.3% of his threes in college and would undoubtedly bolster a Memphis squad that finished in the NBA's bottom third in 3-point percentage in each of the last two seasons.

Walter had an up-and-down freshman year at Baylor, averaging a team-high 14.5 points but shooting only 37.6% from the field. While the McDonald's All-American struggled with his efficiency as the season progressed, the Bears guard's clean shooting mechanics and ability to shoot off screens bodes well for the next level.

Walter also competes hard on the defensive end. He's willing to put his body on the line for charges and apply full-court pressure on opposing ball-handlers. Utah finished dead last in defensive efficiency last season and doesn't really have a stopper on the perimeter.

As the Bulls begin to reshape their backcourt around rising scorer Coby White, a tremendous shooter in McCain could make sense as a partner. McCain is great from long range off the catch (42.1% at Duke) and off the dribble (37%) and should be able to complement White's array of floaters and isolation scoring.

The issue here is defense, where White is still a work in progress. McCain brings disadvantageous size at just 6-foot-2 without great length. He's a sturdy athlete with strength and a knack for steals and crashing the glass, but he isn't big or athletic enough to make up for others' mistakes.

It'll be hard for the Thunder to pass on Cody, especially with the intel they're likely receiving from his brother and Oklahoma City wing Jalen Williams. Sam Presti hasn't been afraid to take a swing in previous drafts, and the Thunder have the luxury to be a bit more patient with him than other teams.

Cody provides size on the wing, passing ability, and can drive all the way to the rim. The 6-foot-8 forward made 41.5% of his threes last season in a limited sample. With his length and high motor, he's got the potential to be a multi-positional defender in the NBA.

Dillingham blends an elite strength of on-ball shot creation with an extreme weakness as an undersized and physically unimposing guard with limited defensive skills. While he needs to work on his rim finishing, his shiftiness with the ball in his hands and ability to finish plays with pull-up jumpers or floaters make him the ideal on-ball guard off the bench. He has the potential to average 15-to-20 points without having to take on a giant defensive assignment.

With the Kings in grave danger of losing Sixth Man of the Year finalist Malik Monk in free agency, Dillingham can seamlessly fill his role as high-scoring up-tempo guard off the pine, bringing an injection of offense either alongside or replacing star point guard De'Aaron Fox.

Carter had a breakout junior year for Providence, averaging 19.7 points, 8.7 rebounds, 3.6 assists, 1.8 steals, and one block across 33 appearances in 2023-24. He earned Big East Player of the Year honors and was a semifinalist for National Defensive Player of the Year.

Carter's ability to contribute in multiple facets of the game should help him earn a role quickly. The Blazers' defense hasn't improved much during the Chauncey Billups era. Adding Carter's on-ball aggression and off-ball instincts to the fold would give Portland some much-needed tenacity.

Collier was ESPN's No. 1 recruit in last season's high school class, but up-and-down play for a wildly disappointing USC squad has raised a lot of questions about his jumper and defensive effort. The defense is an easy fix in the Heat's famous culture, and Collier showed signs of improvement late in the year. But if he can't improve from 67% at the free-throw line and 33.8% from deep, then his value as a physical, oversized guard is diminished.

As a jumbo forward with great mobility, defensive versatility, and a consistent catch-and-shoot jumper, Da Silva is everything teams look for in a complementary power forward in today's NBA. With the 76ers' forward spot looking iffy after a poor postseason from Tobias Harris, Da Silva's strengths off the ball could make him a much better fit alongside Joel Embiid. And with increased on-ball reps, he could reach the ceiling of a stretch-four like Kyle Kuzma.

After back-to-back Player of the Year awards and one of the greatest careers in college basketball history, there's endless talk about how the 7-foot-4 Edey fits in today's NBA. Edey's footspeed at his gargantuan size will always make him a defensive liability, but elite touch down low and the prospect of adding the jumper he showcased at the combine make him a tantalizing offensive big man. With the Lakers looking to find every avenue to win now with an aging LeBron James, Edey's sheer production could be part of the solution.

As the Magic continue to figure out how to optimize former No. 1 pick Paolo Banchero, drafting a do-it-all frontcourt mate in Filipowski could be beneficial. A true 7-footer with the ability to hit threes, score off the dribble, and defend the rim, Filipowski and Banchero combine to check off nearly every box teams seek from their frontcourt. With Wendell Carter Jr. on an affordable deal, the Magic can mix and match him with Filipowski in Year 1.

With a bunch of win-now teams picking in succession, the Raptors end up with one of the best raw prospects in the field with Salaun. The super-long 6-foot-9 wing with terrific mobility screams upper-tier 3-and-D wing and has the size and defensive versatility that Toronto has long craved. As one of the few players still in action - playing in the French playoffs - Salaun has the chance to blow past this projection by the time the draft rolls around.

As demonstrated in their recent playoff series loss to the Celtics, the Cavaliers are in dire need of complementary pieces with multiple strengths, beyond the level of specialist. Tyson flashed point forward potential as a 6-foot-6, wing-sized prospect at Cal this season while also being a 37.2% 3-point shooter on 250 career attempts. He isn't the greatest athlete in the world, but he can still turn himself into a plus defender.

Missi's role in the NBA is already defined: He's a long, athletic rim-runner on offense and a shot-blocker with decent mobility on the other end. Much like players in the mold of Clint Capela or Dereck Lively, Missi can make an impact in the right situation but can't be trusted to make plays with the ball. As Zion Williamson continues to grow as a passer, his ability to make high-low reads for Missi lob dunks could be a nice wrinkle to the Pelicans' offense.

Phoenix is in desperate need of NBA-ready talent to help its Big Three amid a massive salary-cap crunch. If the Suns keep this pick, Holmes' mature game gives them a different look than the current big men on the roster, with a combination of shooting and defensive versatility, plus promising passing chops.

Smith still needs lots of development to become an NBA regular, but his potential comes as a stretch-big with great defensive size and a consistent jumper for his position. Learning under Giannis Antetokounmpo while playing spot minutes as Brook Lopez's understudy is as beneficial a situation for Smith as anywhere in the league. While Milwaukee may look for a win-now player, its lack of future prospects may lead the team to take a swing.

It's long been known that Knicks head coach Tom Thibodeau plays his starters heavy minutes and doesn't often trust rookies, so with back-to-back first-rounders, look for New York to take two different approaches. Carrington is one of the youngest players in the draft and needs to put on significant weight, but his ability to play both on and off the ball with an excellent dribble jumper could help him become a scoring machine in time.

While Carrington is more of a project, McCullar is one of the most seasoned college veterans in this draft and could contribute to the Knicks immediately. McCullar does a little bit of everything with wing size but is most known for his terrific perimeter defense. If he can blend his underrated passing skill with an improving jumper that reached a career-high 34% this season, McCullar's potential is similar to that of current Knicks forward Josh Hart.

Even with Bilal Coulibaly registering a solid rookie campaign, and the No. 2 pick in tow, the rebuilding Wizards should take big swings at high-upside prospects. Klintman's status as a jumbo-sized wing with an effective 3-pointer and perimeter skills make him a clear candidate to put in work with the team's development system. If he can put on weight and grow with on-ball reps in the G League, this pick could pay major dividends.

A former elite high school prospect, Sallis broke out as a junior at Wake Forest with fantastic 49/41/78 shooting splits while playing both on and off the ball. At minimum, Sallis projects as a useful scorer off the bench with good size for a two-guard. However, if he can grow his playmaking skills to pair with his excellent dribble jumper, he has an outside shot at becoming the Timberwolves' long-term point guard with Mike Conley's days dwindling.

Ware may have had the best combine of any first-round prospect, with the monster big man standing at 7-feet with a 7-foot-5 wingspan and ranking in the top three amongst centers in the lane agility, shuttle run, and standing vertical tests. If Ware has the athleticism to hang with guards on the perimeter, and his 42.5% 3-point mark on limited attempts is for real, Ware could be an unfair fit next to three-time MVP Nikola Jokic and his masterful passing.

Few saw George as a one-and-done prospect this season coming over from Switzerland, but he tantalized scouts as an off-ball piece on a veteran Miami team, hitting 40.8% of his 130 threes while flashing defensive tools as a big wing with a 6-foot-10 wingspan. George isn't quite as athletic as similar prospects like Salaun and Klintman, but scouts may prefer his stability as someone who's already proven he can succeed in the 3-and-D role.

At just 5-foot-10, Sears measured as the shortest player at the combine by multiple inches, but there's no questioning his ability as an elite offensive guard. Sears joined Buddy Hield and Doug McDermott as the only players in modern college history to average over 21 points per game while hitting at least 90 threes and 50% of his field goals. Sears was the only one of the three to add four assists per game. With Boston constantly finding new ways to add wrinkles to its offense, betting on Sears' skills makes sense in this spot.

  • NCAA, conferences agree to pay $2.8B settlement
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  • Report: Big 12, ACC vote to approve $2.8B antitrust settlement
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  • ACC commissioner Phillips remains optimistic despite turmoil

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  22. NBA mock draft: Hawks soar for Sarr in post-lottery landscape

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