Simplifying Machine Learning for Inquisitive Developers

Check out the latest articles on Data Analysis & Visualization, Statistics, Practical ML & AI Using Python

Let's explore **z-score tables**, which are used to look up the **cumulative probability** in a standard normal distribution.

First, I'll show you **how to use these tables** to find the cumulative probability **for any z-score from −4 to 4**. Then we'll create them in **Python** using **NumPy, SciPy**, and **pandas**.

In this article, we'll **dive deep into z-score** and its practical applications, such as **comparing data points** across similar distributions, **detecting outliers**, etc.

In this article, I’ll explain **linear equations** step-by-step using simple examples.

You’ll gain an **intuitive understanding** of this fundamental data analysis technique. By the end, you'll be **ready to dive into linear regression**, the first ML algorithem most people encounter.

Let me show you how to **simulate randomness** using **NumPy**, the most widely used **Python** library for numerical computation.

You'll learn how to create a **Random Number Generator (RNG)**, **generate samples** from various statistical distributions, create **random subsets, shuffle arrays**, and much more.

This tutorial provides an introduction to **React's component-driven approach** to building UIs. I'll use practical examples to teach you how to **define and reuse components**.

You'll also learn to specify component **props**, set the **default prop values**, and define **prop types**.

Let's dive deep into **JSX**, a potent mix of **JavaScript** and **HTML** that's used to build interactive **React** applications.

You'll learn how to do **conditional rendering**, apply **CSS styles**, render **arrays**, handle **events**, and much more.

This **step-by-step tutorial** will show you how to **create a new GitHub repository** and upload your local code to it.

You'll also learn how to set up the **essential command line tools** locally and how to use them.

New to **React**? Let me show you how to **create a new app** from scratch and **run it locally**.

You'll also get a glimpse into **creating and using components** to compose a web page, and how to use **React Developer Tools** to debug your app.

Let's explore different ways of selecting data from a **Pandas DataFrame**.

First, I'll introduce the **two types of DataFrame indexes**. Then, I'll show you how to use the methods **iloc[]** and **loc[]** to access the **DataFrame** data.

Let me show you how to use the methods **idxmin()** and **idxmax()** to get the index of the minimum or maximum value.

These methods provide additional functionality for **DataFrames**. We'll cover that as well.