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Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.
Recommendation engines are a common use case for machine learning. Other popular uses include fraud detection, spam filtering, malware threat detection, business process automation (BPA) and predictive maintenance.
Why is machine learning important?
Machine learning is important because it gives enterprises a view of trends in customer behavior and business operational patterns, as well as supports the development of new products. Many of today's leading companies, such as Facebook, Google and Uber, make machine learning a central part of their operations. Machine learning has become a significant competitive differentiator for many companies.
Mechanical Engineering Department
B. Tech, VIth Semester
Make-Up Examination, (2020-21) Even Semester
(NDT) (KME 061)
1. Attempt all the questions
2. The question paper consist of 50 Questions
3. The duration of question paper is 90 minutes
4. The correct question will have a weightage of +2 marks
5. wrong answer has the weightage of 0 mark
6. Unattempted question fetches zero marks
This course provide basic understandings of management processes and the concepts of organizational behaviour .Further, it helps in applying the concepts of management and organizational behaviors in real world situations. Moreover, it creates an environment to familiarizing the students with the contemporary issues in management.
The objective of this course is to develop the ability to apply the concepts, tools and techniques
of economics in analysing and interpreting business decisions.
- To understand the basic concepts of Marketing Analytics
- To study various tools to have marketing insights in various marketing areas through empirical data
- To interpret the marketing data for effective marketing decision making
- To draw inferences from data in order to answer descriptive, predictive, and prescriptive questions relevant to marketing managers
Course Objectives
1. Assess market opportunities by analyzing customers, competitors, collaborators, context, and the strengths and weaknesses of a company.
2. Understand consumers’ requirements and their behaviors.
3. Develop effective marketing strategies to achieve organizational objectives.
4. Communicate and defend your recommendations and critically examine and build upon the recommendations of your classmates both quantitatively and qualitatively.
5. Develop the understanding the current global and digital aspect of marketing.
Course Objectives
1. Assess market opportunities by analyzing customers, competitors, collaborators, context, and the strengths and weaknesses of a company.
2. Understand consumers’ requirements and their behaviors.
3. Develop effective marketing strategies to achieve organizational objectives.
4. Communicate and defend your recommendations and critically examine and build upon the recommendations of your classmates both quantitatively and qualitatively.
5. Develop the understanding the current global and digital aspect of marketing.
CO1 Apply and analyze the nature and scope of services marketing
CO2 Critical analysis to perceive service shortcomings in reference to ingredients to create service excellence
CO3 Apply and evaluate critical issues related to service design
CO4 Analyze theoretical and practical basis for evaluating and developing service performance using company examples
CO5 Illustrate and assess characteristics and challenges of managing
service firms in the modern world
Materials Science is an interdisciplinary field involving the properties of matter and its applications to various areas of science and engineering. It includes elements of applied physics and chemistry, as well as chemical, mechanical, civil and electrical engineering
KAS 103T ENGINEERING MATHMATICS I
3L:1T:0P 4 Credits
COURSE OBJECTIVE: The objective of this course is to familiarize the graduate engineers with techniques in calculus, multivariate analysis, vector calculus and linear algebra. It aims to equip the students with standard concepts and tools from intermediate to advanced level that will enable them to tackle more advanced level of mathematics and applications that they would find useful in their disciplines. The students will learn: To apply the knowledge of differential calculus in the field of engineering. To deal with functions of several variables that is essential in optimizing the results of real life problems. Multiple integral tools to deal with engineering problems involving centre of gravity, volume etc. To deal with vector calculus that is required in different branches of Engineering to graduate engineers. The essential tools of matrices and linear algebra, Eigen values and diagonalization in a Comprehensive manner are required.
Unit I Matrices: Types of Matrices: Symmetric, Skew-symmetric and Orthogonal Matrices; Complex Matrices, Inverse and Rank of matrix using elementary transformations, Rank-Nullity theorem; System of linear equations, Characteristic equation, Cayley-Hamilton Theorem and its application, Eigen values and eigenvectors; Diagonalisation of a Matrix 8
Unit II Differential Calculus- I: Introduction to limits, continuity and differentiability, Rolle’s Theorem, Lagrange’s Mean value theorem and Cauchy mean value theorem, Successive Differentiation (nth order derivatives), Leibnitz theorem and its application, Envelope of family of one and two parameter, Curve tracing: Cartesian and Polar co-ordinates
Unit III Differential Calculus-II: Partial derivatives, Total derivative, Euler’s Theorem for homogeneous functions, Taylor and Maclaurin’s theorems for a function of two variables, Maxima and Minima of functions of several variables, Lagrange Method of Multipliers, Jacobians, Approximation of errors
Unit IV Multivariable Calculus-I: Multiple integration: Double integral, Triple integral, Change of order of integration, Change of variables, Application: Areas and volumes, Center of mass and center of gravity (Constant and variable densities)
Unit V Vector Calculus: Vector identities (without proof), Vector differentiation:
Gradient, Curl and Divergence and their Physical interpretation, Directional
derivatives.
Vector Integration: Line integral, Surface integral, Volume integral, Gauss’s
Divergence theorem, Green’s theorem and Stoke’s theorem (without proof)
and their applications
MATHEMATICS-II
Medicinal Chemistry II includes study of the development of various classes of drugs, classification, mechanism of action, uses of drugs mentioned in the course, Structure activity relationship of selective class of drugs as specified in the course and synthesis of drugs superscripted (*) in the syllabus.
A microcontroller is a compact integrated circuit designed to govern a specific operation in an embedded system. A typical microcontroller includes a processor, memory and input/output (I/O) peripherals on a single chip.
The microcontroller is designed for a specific task or to perform the assigned task repeatedly. Once the program is embedded on a microcontroller chip, it can’t be altered easily and you may need some special tools to reburn it. As per application, the process is fixed in microcontroller. Hence, the output depends on the input given by the user or sensors or predefined inputs.
The microprocessor is useful in very intensive processes. It only contains a CPU (central processing unit) but there are many other parts needed to work with the CPU to complete a process. These all other parts are connected externally.
The Mini Project is an integral part of the curriculum designed to provide students with hands-on experience in applying theoretical knowledge to practical problems. It bridges the gap between classroom learning and real-world applications, encouraging creativity, teamwork, and problem-solving skills.
- Teacher: Mr. Harsh Modi [CSE]