In this article we are going to work on JS version that uses “addEventListener” method instead of the “onclick” in HTML, which is perhaps considered more primitive and suitable for complete beginners. The code bellow already has the possibility to adds tasks to the list, and a complete and delete button. What we’ll now add is:

• A saveTasks() function to store the tasks in local storage.
• A loadTasks() function to load saved tasks when the page loads.

This means we will update the existing code to save changes whenever a task is added, completed, or deleted, even after the browser window is closed or refreshed.

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In this article we’re going to build on our previous project: 3 JavaScript versions of simple to-do list. Let’s try adding a new useful feature – let’s save the task we add to local storage. Local Storage is a feature in your browser that lets you save data, in our case — tasks — even after the page is refreshed or the browser is closed and reopened.

In this article we will be using onclick in HTML, which is probably the easiest method to understand for complete beginners. You simply attach the addTask() function directly to the button using the onclick attribute inside the HTML. While this works fine for small projects, it’s not considered best practice because it mixes your structure (HTML) with your behavior (JavaScript), which can make your code harder to manage in the long run. We will focus on better practices
in our next article.
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Creating a simple to-do list is one of the best beginner-friendly JavaScript projects. It helps you practice how to connect HTML structure, CSS styling, and JavaScript functionality.

In this article, I’ll walk you through four different ways to create a to-do list using JavaScript. Each method starts with the same HTML and CSS, but the JavaScript code will vary slightly. This way, you’ll learn different techniques and understand the pros and cons of each.

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Distortions in AI-generated videos can be technically referred to as artifacts or generative artifacts. These are unintended visual or auditory anomalies that occur due to limitations in the AI model, training data, or generation process. Common types of distortions include:

Standardizing data is a vital part of the data cleaning process. It guarantees consistency and uniformity within the dataset, which is essential for precise analysis, reporting, and machine learning models, leading to optimal data integrity. Depending on the data’s nature and the analysis requirements, standardizing data can involve a variety of transformations and operations. The main aspects of data standardization include:
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Removing duplicates in MySQL involves identifying and deleting rows with duplicate data to ensure the integrity and accuracy of your database. This article will serve as a step-by-step guide on how to remove duplicates in MySQL.
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Handling missing values is a critical step in data preprocessing, particularly in data science and machine learning projects, because many algorithms do not function properly or may produce misleading results if the data contains missing or null values. Let’s take a look at the key strategies and considerations for handling missing data.
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Data cleaning is an essential step in the data analysis process. It involves preparing and transforming raw data into a more useful and accurate format. SQL (Structured Query Language) is a powerful tool for data cleaning because it can handle large datasets efficiently and provides various functions and operations to manipulate data.
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Choosing between Retrieval-Augmented Generation (RAG) and fine-tuning depends on the specific requirements, resources, and goals of your application. Here are scenarios when each approach is more sensible.

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Retrieval-Augmented Generation (RAG) and fine-tuning are two approaches used in the development and enhancement of language models. Each has its own strengths, applications, and considerations. Here’s a detailed comparison. Let’s have a look. …