Indian Institute of Technology Madras

“S2_VOL2_JOINTCONTSDISTRIBUTIONS.pdf” is a focused academic resource tailored for IIT Madras BS Data Science students, covering the topic of joint continuous distributions in advanced statistics. The document opens by distinguishing continuous random variables from discrete types, emphasizing practical applications and the need for probability calculations over intervals rather than fixed points. With rich, step-by-step explanations, it introduces the concepts of cumulative distribution func...

“S2_VOL2_JOINTCONTSDISTRIBUTIONS.pdf” is a focused academic resource tailored for IIT Madras BS Data Science students, covering the topic of joint continuous distributions in advanced statistics. The document opens by distinguishing continuous random variables from discrete types, emphasizing practical applications and the need for probability calculations over intervals rather than fixed points. With rich, step-by-step explanations, it introduces the concepts of cumulative distribution func...

“S2_VOL2_JOINTCONTSDISTRIBUTIONS.pdf” is a focused academic resource tailored for IIT Madras BS Data Science students, covering the topic of joint continuous distributions in advanced statistics. The document opens by distinguishing continuous random variables from discrete types, emphasizing practical applications and the need for probability calculations over intervals rather than fixed points. With rich, step-by-step explanations, it introduces the concepts of cumulative distribution func...

“S2_VOL2_JOINTCONTSDISTRIBUTIONS.pdf” is a focused academic resource tailored for IIT Madras BS Data Science students, covering the topic of joint continuous distributions in advanced statistics. The document opens by distinguishing continuous random variables from discrete types, emphasizing practical applications and the need for probability calculations over intervals rather than fixed points. With rich, step-by-step explanations, it introduces the concepts of cumulative distribution func...

A focused academic resource tailored for IIT Madras BS Data Science students, covering the topic of joint continuous distributions in advanced statistics. The document opens by distinguishing continuous random variables from discrete types, emphasizing practical applications and the need for probability calculations over intervals rather than fixed points. With rich, step-by-step explanations, it introduces the concepts of cumulative distribution function (CDF) and probability density function (...

Its a document which gives basic and best idea of python coding language

These are the notes of all 6 lectures of first week of Machine Learning Foundations course. L1 - What is Machine Leaning? l2 - Data, Models and ML Task l3 - Supervised Learning: Regression l4 - Classification l5 - Unsupervised Learning: Dimensionality Reduction l6 - Unsupervised Learning: Density Estimation

These class notes consist of topics that were taught for the course "Computer Methods in Civil Engineering" by Prof. Subhadeep Banerjee. The topics that are covered in these notes are Dirichlet & Newman Condition (Essential Forced & Natural Boundary Condition), Gauss Elimination Method, LU Decomposition, Pivoting, Norm, Jacobi Method of Iteration, Gauss Siedel Method, Jacobi Method, Successive Over Relaxation Method (SOR), 1D & 2D Newton Raphson Method, Initial Value Problems: Euler Implicit &...

Data structures are ways of organizing and storing data in a computer so that it can be accessed and modified efficiently. Some common data structures include arrays, linked lists, queues, stacks, trees, and graphs. Each data structure has its own set of characteristics and trade-offs, and the choice of which data structure to use depends on the specific requirements of a given problem or application. Notes on data structures typically include information on the characteristics, operations, and ...

Class Notes for Oe4300 course ocean energy