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This video explains the concepts of maximum and minimum values of a function through an example, in which we try to design a cost-effective water tank (made of glass) with a square base and an open top that can hold 1 gallon of water.

This video explains how to find the local and absolute minimum and maximum values of a function, using the critical numbers, and the first and second derivative tests.

This video briefly explain the Taylor and Maclaurin series and some of their key applications. Another relevant video (which uses the first degree Taylor Polynomial): Linear approximation of a function f near or around a point (th-cam.com/video/cwx5aTyvFIc/w-d-xo.html)

This video explains the linear approximation of a non-linear function f at or around a point, a. An example is also solved to show how the method works. Newton-Raphson (Root finding methods): th-cam.com/video/RAJ-d0O1acc/w-d-xo.html

This video explains the Conjugate Gradient Method for solving a system of linear equations, and provides the corresponding Python code, which is used to solve an example problem.

This video explains the Gauss-Seidel method for solving the system of linear equations and provides the corresponding Python code, which is used to solve an example problem.

This video explains Cholesky's LU decomposition and walks us through the corresponding Python code which is used to solve the example problems.

This video explains the Crout's decomposition method and provides its Python code which is used to solve an example curve fitting problem. The previous two videos on LU decomposition are as follows: 1. LU Decomposition (th-cam.com/video/Fz3dD-3xet4/w-d-xo.html) 2. Doolittle's (LU) Decomposition Method with a Python Code (th-cam.com/video/VlBSN221qd8/w-d-xo.html)

This video explains Doolittle's decomposition and how we can use it to solve a system of linear equations. The python code for this method has been discussed and used to solve a curve fitting problem. Please also check the previous video on LU decomposition methods th-cam.com/video/Fz3dD-3xet4/w-d-xo.html

This video explains how LU decomposition works. In the coming videos, we'll explain Doolittle's, Crout's and Choleski's decompositions in more detail using Python code.

This video explains the Gauss-Jordan elimination method, which is an extension of the Gauss elimination method (th-cam.com/video/bWpUXyCubhI/w-d-xo.html). The python code for the method is explained and is used to solve a curve fitting problem.

This video explain the Gauss Elimination method for solving a system of linear equations. The python code for this method is also discussed and used to solve a curve fitting problem.

This video contains an introduction to system of linear equations. An example with two equations and two unknowns is solved and visualized in Python (code snippets shared in the video). In the coming videos, we will look into different direct and iterative methods, including Gauss-Elimination, LU Factorization, Gauss-Seidel and Conjugate Gradient methods. We'll write and discuss the Python code...

This video explain how to build a statistics app from scratch using Python's Tkinter package. The users will be able to compute different statistics and display the results as a table and also create histogram, box and whisker and scatter plots from the input data. The users will also be able to save the plotted charts.

Vector Analysis using Python: Part 5 - Line, Surface and Volume Integrals

Vector Analysis using Python: Part 4 - Gradient, Divergence and Curl

Vector Analysis using Python: Part 3 - Differentiation

Vector Analyis using Python: Part 2 - Dot (scalar) and Cross (vector) Products

Vector Analysis using Python: Part 1 - Introduction

Enhancing Image Classification Performance with Transfer Learning in PyTorch

Image Classification (from project structure to inference) using PyTorch in less than 10 mins

Root finding methods: Secant and Modified-secant

Root finding methods: Newton-Raphson

Root finding methods: Fixed point iteration

Root finding methods: False position

Root finding methods: Bisection

Root finding methods: Incremental search

Root finding methods: Introduction

Learn Pandas by Solving Problems