Python Operators

Python operator is a symbol that performs an operation on one or more values or variables. For example, the addition operator + adds two numbers together, the subtraction operator - subtracts one number from another, and so on. Python provides various types of operators such as arithmetic operators, comparison operators, logical operators, assignment operators, etc., each serving a specific purpose in manipulating data or controlling program flow.

Build a Calculator app using Python

"Explore the world of Python programming with our comprehensive calculator tutorial, compatible with both Python 2 and Python 3. Delve into the fundamentals of arithmetic operations and user input handling, learning how to create a functional calculator application. Whether you're a novice or experienced coder, this tutorial provides step-by-step guidance to master the art of calculator programming in Python."

Creating & Visualizing Neural Network

Have you ever wondered what goes on inside a machine that can learn? In this blog, we'll be diving into the world of neural networks by building a simple one ourselves! Using the powerful Keras API, we'll step-by-step craft a very simple neural network and visualize it with the Netron visualizer tool.

Python Control Structures

Python first evaluates the if condition. If it's true, it executes the corresponding block of code and skips the elif and else blocks. If it's false, it moves to the next condition specified by elif. If that's true, it executes the corresponding block and skips the else block. If neither the if nor the elif conditions are true, the else block is executed. This demonstrates the sequential evaluation and branching behavior provided by if, elif, and else in Python.

Data Types in Python

Python data types are crucial for structuring and managing information in programs. They provide a framework for handling diverse data, including integers, floats, strings, lists, dictionaries, and booleans. By leveraging these data types effectively, developers can optimize memory usage, streamline operations, and ensure code reliability in Python applications.