## Blog

### Mastering Central Limit Theorem (CLT) with Intuitive Examples

Let’s explore the Central Limit Theorem (CLT) with an example of rolling two dice multiple times (let’s say 30 times). We will calculate the mean of the two dice values and plot its distribution to understand the CLT intuitively. Round 1: We roll the dice and get 2 and 5.

### Why does a 20 year old have access to TS/SCI and what do we do about it?

This is not the first time a young person has had authorized access to substantial amounts oftop secret sensitive compartmented information (TS/SCI) and leaked it. How could thishappen? It’s easy to understand… What do 20-year old people do in the military? Among other things, they are in the field being

### Demystifying Degrees of Freedom with Visual Examples: A Beginner’s Guide

The concept of degrees of freedom is essential in statistical analysis, and it is commonly used in various statistical tests. In this blog post, we will explore A) Without any restriction B) With a restriction C) Degrees of freedom in contingency tables D) Bessel’s correction  with examples. This will help

### A Beginner’s Guide to t-tests: Real-life Applications of t-test: One-Sample, Two Sample and Paired Sample t-test

William Sealy Gosset, an English statistician who was also a beer brewer, developed the t-test. He used this test to ensure the consistency and quality of the beer he produced. Gosset published his work under the pseudonym “Student”, which is why the t-test is also known as the Student’s t-test.

### Basics of Blockchain Technology

Blockchain technology has gained popularity in recent times. This article covers some of the fundamental concepts associated with it, including: What is blockchain? Why do we need blockchain? How does blockchain ensure trust? Who invented it? When to use it? When not to use it? So, let’s get started. What

### Naïve Bayes Classification Model for Natural Language Processing Problem using Python

Learn how to apply a Naïve Bayes classification model to solve a Natural Language Processing (NLP) problem in Python in this article. Here are the steps we will cover: Download a sample dataset Split the dataset into test and train data Vectorize the data Build and measure the accuracy of

### So you’re looking for a cyber security board member for your public company

Good luck finding someone qualified… The SEC is apparently about to make it a requirement for public companies to report on “the board of directors’ cybersecurity expertise, if any, and its oversight of cybersecurity risk”.1 Some details: Why would it be hard to find someone like this? But here’s the

### The Threat Environment

People who don’t have to do it seem to not understand the nature of the cyber threat. This very short summary is intended for everyone who is responsible for it to hand to everyone else to help start a conversation and gain mutual understanding. The 6 questions people are commonly

### Experiential Learning

AI, Neural Nets, and Complexity of the Brain Quantum cryptography and its real effect on current systems Will training help to counter influence operations? Blockchain, distributed ledger, and crypto-currency Don’t trust zero trust Basics of complexity and granularity and tradeoffs of space and time Granularity of control and adding dimensions

### Some results in cybersecurity and why they may be interesting

Every once in a while I come across something interesting with substantial potential impacts but that differs from the common misconceptions. Many of them I point out with a fevered disdain of foolishness, while others I view more philosophically. This article is about some recent results that I think are

### Cyberwarfare: Evolution & Impact

In the late twentieth century, the widespread use of the Internet revolutionized the speed at which information was collected, computed, and shared. Suddenly, the standard

### Evolution and Future of Digital Learning

In recent years, technology has exponentially advanced beyond automobiles or basic electricity in cities. It has permeated every aspect of our modern world, forcing today’s

### Deep Learning Basics

Deep learning is a powerful machine learning technique. These are widely used in Natural Language Processing (NLP) image/speech recognition robotics and many other artificial intelligence

### Building a Deep Learning Model

Building a Deep Learning Model using Keras In this post, let us see how to build a deep learning model using Keras. If you haven’t

### Confusion Matrix

Confusion Matrix, Accuracy, Precision, Recall, F score explained with an example In this post, we will learn about What is accuracy What are precision, recall,

### Pre-processing

Data Preprocessing – Creating Dummy Variables and Converting Ordinal Variables to Numbers with Examples Data cleaning is a critical step before fitting any statistical model.

### Missing Values

Handling Missing Values in Python In this post, we will discuss: How to check for missing values Different methods to handle missing values Real life

### Time Series Components

Components of Time Series In this post, let us explore the four components of time series data. Trend (T) Cyclicality (C) Seasonality (S) Irregular component

### ARIMA/SARIMA with Python

Autoregressive Integrated Moving Average (ARIMA) is a popular time series forecasting model. It is used in forecasting time series variable such as price, sales, production,