Python Quiz of the Day

Python Coding Challenge - Question with Answer (ID 070826)

Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-070826.html

🚀 FREE AI & Machine Learning PDF Alert!
📘 Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
📄 160 Pages (Your free PDF edition)
Want to understand the mathematics behind modern AI? This book explores the foundations of Geometric Deep Learning, covering concepts such as:
✅ Graph Neural Networks (GNNs)
✅ Convolutional Neural Networks (CNNs)
✅ Transformers from a geometric perspective
✅ Symmetry, groups, and invariance
✅ Graphs, grids, manifolds, geodesics, and gauges
Whether you're a Machine Learning Engineer, AI Researcher, Data Scientist, or Computer Science student, this is a valuable resource to deepen your understanding of next-generation deep learning architectures.
📥 Download the FREE PDF: https://www.clcoding.com/2026/08/geometric-deep-learning-grids-groups.html

🎉 Hello everyone! Welcome to Day 7 of our FREE August Python Bootcamp! 🐍

It's great to see all of you here today. Whether you've been with us since Day 1 or you're joining for the first time, you're most welcome!

Today we'll continue learning Python through live coding, practical examples, and hands-on exercises. Keep your laptop ready, code along with me, and feel free to ask your questions in the live chat.

If you're finding this bootcamp helpful, don't forget to Like the stream, Subscribe to the channel, and Share this live with your friends who want to learn Python.

Join Free: https://youtube.com/live/j_86vQ6DHHI?feature=share

Let's make Day 7 another productive session. Happy coding, and let's get started! 🚀💻

🚀 FREE PDF for Machine Learning Enthusiasts!

📘 Inference in Statistical Modelling and Machine Learning: A Concise Introduction

Want to build a strong foundation in Statistical Modeling, Machine Learning, and Bayesian Inference? This excellent free resource covers the mathematical concepts and practical ideas behind modern AI and ML in a beginner-friendly yet rigorous way. The companion site also includes Python notebooks, solutions, and lecture slides.

📚 You'll learn:
✅ Supervised & Unsupervised Learning
✅ Probability, Likelihood & Bayes
✅ Frequentist vs Bayesian Inference
✅ Linear Regression & Classification
✅ Neural Networks & Deep Learning
✅ Graphical Models & Regularization
✅ Core Statistical Foundations for AI

🔗 Read & Download(PDF Book for Free):
https://www.clcoding.com/2026/08/inference-in-statistical-modelling-and.html

💡 If you're preparing for a career in Data Science, Machine Learning, or Artificial Intelligence, this is a must-read resource.

Where Am I?” — Build a Location Compass with Python

📘 Free PDF Book Alert!

Understanding Machine Learning: From Theory to Algorithms 🤖📚

A 449-page resource for anyone looking to build a stronger foundation in Machine Learning—from fundamental theory to important algorithms.

🔹 449 Pages
🔹 Machine Learning fundamentals
🔹 Theory + Algorithms
🔹 Great for students, developers & AI/ML enthusiasts
🔹 Useful for self-study and interview preparation

Get the free PDF: https://www.clcoding.com/2026/07/understanding-machine-learning-from.html

Increasing Star Triangle ⭐️
🔥 Master Python Patterns: Start With This Simple Triangle!
Pattern problems are one of the best ways to strengthen your Python loops. 🐍
Start with the increasing star triangle and understand for loops step by step.
Save this for your Python interview preparation! 💾
107 Pattern Plots Using Python
https://pythonclcoding.gumroad.com/l/vcssjo

🚀 Day 8 – Object-Oriented Programming (Part 1)* 🐍

Today we’re taking Python to the next level with OOP!

We’ll learn:
✅ OOP Introduction
✅ Classes & Objects
✅ Constructors & self
✅ Instance Variables & Methods
✅ Class Variables
✅ Static Methods
✅ Class Methods

💻 Join the LIVE session today at 3:30 PM CEST! https://youtube.com/live/mfHhsYQJW5s?feature=share

Python Quiz of the day.

Python Coding Challenge - Question with Answer (ID 080826)

Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-080826.html

📘 The Many Faces of Information Geometry — Free PDF

Explore Information Geometry, a fascinating field connecting geometry, statistics, probability, information theory, and machine learning.

📖 Book: The Many Faces of Information Geometry

📥 Free PDF: Read / Download the Free PDF
https://www.clcoding.com/2026/08/the-many-faces-of-information.html

A useful resource for students, researchers, and anyone interested in the mathematical foundations of statistics, information theory, and machine learning.

🔖 Free PDF Book Alert
📚 Save it for your learning and research collection.

🎬 Movie Popularity Meter Using TMDB API

Here’s a simple Python project that fetches movie information from The Movie Database (TMDB) API and creates a Popularity Meter based on the movie's TMDB popularity score.

What it does

Takes a movie name as input

Searches TMDB

Gets the movie's:Title

Release date
Rating
Vote count
Popularity score
Overview

https://amzn.to/4xoUeeh

Displays a visual popularity meter

1/9 TensorFlow Cheat Sheet Thread

Want to learn TensorFlow but don’t know where to start?

I created a TensorFlow Cheat Sheet covering the essentials—from tensors and operations to datasets, model training, and the complete workflow.

🧵 Let’s break it down 👇 https://x.com/clcoding/status/2086369371149267318

🚀 Day 9 – Object-Oriented Programming (Part 2) 🐍

We’re going deeper into Python OOP today!

🔥 Today’s Topics:

Inheritance
Polymorphism
Method Overriding
super()
Multiple Inheritance
Encapsulation
Abstraction
Property Decorators
Magic Methods
Practical Examples

🔴 LIVE Today at 3:30 PM CEST

https://youtube.com/live/fo6_qEPhI6s?feature=share

Python Quiz of the Day

Python Coding Challenge - Question with Answer (ID 090826)

Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-090826.html

📚 Scales of Fréchet Means and Karcher Quasi-Arithmetic Means

A fascinating mathematical resource exploring Fréchet means, Karcher means, and quasi-arithmetic means—useful topics in geometry, statistics, optimization, and data analysis on non-Euclidean spaces.

📖 Free PDF:
https://www.clcoding.com/2026/08/scales-of-frechet-means-and-karcher.html

If you're interested in mathematics, statistics, geometric data analysis, or advanced machine learning, this is a useful paper/book to explore.

5 Practical psutil python programs

1. 💻 CPU, RAM & Disk Usage
Monitor your system’s CPU, RAM, and disk usage in real time with Python. A simple way to understand your computer’s resource consumption using psutil.

2. 🔥 Top 5 Memory-Hungry Processes
Find which processes are consuming the most RAM on your system. Perfect for quickly identifying memory-heavy applications with Python.

3. 🌐 Network Upload & Download
Track how much data your computer has uploaded and downloaded. Use psutil to monitor network activity directly from Python.

4. 🔋 Battery Status
Check your laptop’s current battery percentage and charging status. A handy Python script for monitoring battery health at a glance.

5. ⚙️ Live System Information
Get essential system details such as OS, processor, CPU cores, and boot time. Build a quick system-information dashboard using Python.

https://x.com/clcoding/status/2086653087167775194?s=20

📘 Deep Learning with Python, Second Edition — Free PDF

Deep Learning with Python, Second Edition by François Chollet — 504 pages.

The official publisher confirms the book is 504 pages, published in 2021, and covers deep learning with Python, Keras, and TensorFlow.

📚 Topics include:

Deep Learning fundamentals
Neural networks
Keras & TensorFlow
Computer vision
Image classification & segmentation
Time-series forecasting
NLP & text classification
Machine translation
Generative deep learning
Image generation
Neural style transfer

🔗 Free PDF post: https://www.clcoding.com/2025/05/deep-learning-with-python-second.html

Python Quiz of The Day

Python Coding Challenge - Question with Answer (ID 100826)

Answer with Explanation: https://www.clcoding.com/2026/08/python-coding-challenge-id-090826_01859501803.html