# Lecture Notes

### Log Barrier Minimization: An Intuitive Approach

This post deals with the minimization of the log barrier function that is:     where defined as     We shall attempt an intuitive explanation on the solution of the following unconstrained minimization problem     First off, let’s say our set of inequalities defined by is closed, the […]

### Selenium Automation on Python

The Selenium Python package is automates web driver interaction via Python. Selenium provides a simple API to write functional tests using WebDriver. Selenium Python bindings provide a convenient API to access Selenium WebDrivers like Chrome, Safari, Firefox, Opera, Edge, Blackberry, and many more. This lecture aims at covering all related […]

### NVIDIA Jarvis Conversational AI on Python

“True conversational AI is a voice assistant that can engage in human-like dialogue, capturing context and providing intelligent responses. Such AI models must be massive and highly complex,” Sid Sharma from ‘What Is Conversational AI?’. This lecture attempts to demystify conversational AI by covering its counterparts that include, but not […]

### Markowitz Portfolio Optimization in Stock Market Analysis

The following lecture talks about the Markowitz Portfolio Optimization problem in convex optimization. Indeed, many variants of this problem exists, but the classical one looks like this     where is an sized vector containing the amount of assets to invest in. The vector is the mean of the relative […]

### Soft & Hard Margin Support Vector Machine (SVM)| Machine Learning with TensorFlow & scikit-learn

ðŸ“šAbout This lecture focuses on the theoretical as well as practical aspects of the Support Vector Machines. It is a supervised learning model associated with learning algorithms that analyze data used for classification and regression analysis. Developed at AT&T Bell Laboratories by Vapnik with colleagues (Boser et al., 1992, Guyon […]

### Introduction of Convex Optimization

Mathematical optimization is a problem that takes the following form (1)   where is a vector containing all the variables of the problem (2)   The function is referred to as the cost or the objective function. Moreover, the functions are referred to as constraint functions. In most cases, our […]

### Strong Alternatives

The above lecture is brought to you by Skillshare. In a previous post of mine, we introduced weak alternatives. As a small reminder, consider the following two sets (1)   and (2)   where (3)   is the dual function and is the domain of the problem. Since we did […]

### MATPLOTLIB in one video

This tutorial is brought to you by DataCamp. The tutorial does the most in rigorously explaining the little bits and pieces of the wonderful Matplotlib. Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things easier. Contents of […]

### Weak Alternatives

Let us say we are interested in checking whether system hereby defined as (1)   is feasible or not. In other words, could we find a vector that satisfies set ? In many cases, it may turn out to be hard to answer the question by exhaustively searching all possible […]

### Perturbation & Sensitivity Analysis

In this lecture, we talk about Perturbation and Sensitivity Analysis. But what does that mean ? Well, consider our good old looking optimization problem that looks like this (1)   One way to tell how the above problem reacts to perturbation is to actually perturb it and check how its […]