Hello Learners, In this Post, you will find NPTEL Data Science for Engineers Assignment 5 Week 5 Answers 2023. All the Answers are provided below to help the students as a reference don’t straight away look for the solutions.NPTEL Data Science for Engineers Assignment 6 Answers Join Group👇 CLICK HERENote: First try to solve the questions by yourself. If you find any difficulty, then look for the solutions.COURSE NAMEANSWERNPTEL Data Science for Engineers Assignment 1 AnswersClick HereNPTEL Data Science for Engineers Assignment 2 AnswersClick HereNPTEL Data Science for Engineers Assignment 3 AnswersClick HereNPTEL Data Science for Engineers Assignment 4 AnswersClick HereNPTEL Data Science for Engineers Assignment 5 AnswersClick HereNPTEL Data Science for Engineers Assignment 6 AnswersClick HereNPTEL Data Science for Engineers Assignment 7 AnswersClick HereNPTEL Data Science for Engineers Assignment 8 AnswersClick HereNPTEL Data Science for Engineers Assignment 5 Answers 2023NPTEL Data Science for Engineers Assignment 5 Answers 2023:We are updating answers soon Join Group for update: CLICK HEREQ.1. Which of the following statements is/are not TRUE with respect to the multi variate optimization?I – The gradient of a function at a point is parallel to the contours II – Gradient points in the direction of greatest increase of the function III – Negative gradient points in the direction of the greatest decrease of the function IV – Hessian is a non-symmetric matrixIII and IIII and IV III and IVQ.2. The solution to an unconstrained optimization problem is always the same as the solution to the constrained one.TrueFalseQ.3. Gradient based algorithm methods computeonly step length at each iterationboth direction and step length at each iteration only direction at each iterationnone of the aboveNPTEL Data Science for Engineers Assignment 6 Answers Join Group👇 Q.4. For an unconstrained multivariate optimization given f(x¯¯¯), the necessary second order condition for x¯¯¯∗ to be the minimizer of f(x) is∇2f(x¯¯¯∗) must be negative definite.∇2f(x¯¯¯∗) must be positive definite. ∇f(x¯¯¯∗)=0f”(x¯¯¯∗)>0Use the following information to answer Q5, 6, 7 and 8minx1,x2∈R f(x1,x2)=x21+4×22−2×1+8×2.Q.5. Which among the following is the stationary point for f(x1,x2)?(0,0)(1,−1) (−1,−1)(−1,1)Q.6. Find the eigen values corresponding to Hessian matrix of f.1,−11,12,8 0,2Q.7. Find the minimum value of f.0-5-1 1NPTEL Data Science for Engineers Week 5 Answers Join Group👇 CLICK HEREQ.8. What is the minimum value of f(x1,x2) subject to the constraint x1+2×2=7?-5-1270Q.9. Find the maximum value of f(x,y)=49−x2−y2 subject to the constraint x+3y=10.49 465939Q.10. Consider an optimization problem minx1,x2 x2−xy+y2 subject to the constraints2x+y≤1x+2y≥2x≥−1Answer: CNPTEL Data Science for Engineers Assignment 5 Answers Join Group👇 Disclaimer: This answer is provided by us only for discussion purpose if any answer will be getting wrong don’t blame us. If any doubt or suggestions regarding any question kindly comment. The solution is provided by Brokenprogrammers. This tutorial is only for Discussion and Learning purpose.About NPTEL Data Science for Engineers Course:Learning Objectives :Introduce R as a programming language Introduce the mathematical foundations required for data science Introduce the first level data science algorithms Introduce a data analytics problem solving frameworkIntroduce a practical capstone case studyLearning Outcomes:Describe a flow process for data science problems (Remembering) Classify data science problems into standard typology (Comprehension)Develop R codes for data science solutions (Application) Correlate results to the solution approach followed (Analysis)Assess the solution approach (Evaluation) Construct use cases to validate approach and identify modifications required (Creating) Course Layout:Week 1: Course philosophy and introduction to R Week 2: Linear algebra for data science 1. Algebraic view – vectors, matrices, product of matrix & vector, rank, null space, solution of over-determined set of equations and pseudo-inverse) 2. Geometric view – vectors, distance, projections, eigenvalue decompositionWeek 3: Statistics (descriptive statistics, notion of probability, distributions, mean, variance, covariance, covariance matrix, understanding univariate and multivariate normal distributions, introduction to hypothesis testing, confidence interval for estimates) Week 4: OptimizationWeek 5: 1. Optimization2. Typology of data science problems and a solution frameworkWeek 6: 1. Simple linear regression and verifying assumptions used in linear regression 2. Multivariate linear regression, model assessment, assessing importance of different variables, subset selectionWeek 7: Classification using logistic regressionWeek 8: Classification using kNN and k-means clusteringCRITERIA TO GET A CERTIFICATE:Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.Exam score = 75% of the proctored certification exam score out of 100Final score = Average assignment score + Exam scoreYOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.If you have not registered for exam kindly register Through https://examform.nptel.ac.in/ Post navigationNPTEL Air Pollution and Control Assignment 5 Answers 2023 NPTEL Introduction to Machine Learning Assignment 5 Answers 2023