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| 06 октября | +1 | |||
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Посты канала
🚀 Learn Machine Learning with Microsoft Azure
Want to build and deploy machine learning models using Azure?
This course, “Create Machine Learning Models in Microsoft Azure,” is part of the Microsoft Azure Data Scientist Associate (DP-100) Exam Prep Professional Certificate.
You’ll get hands-on experience with Azure Machine Learning and learn skills that are useful for real-world ML workflows.
Starts Oct 6 • Enroll for free
https://www.clcoding.com/2024/01/create-machine-learning-models-in.html
A great resource if you're preparing for DP-100 or exploring cloud-based machine learning.
| 2 |  Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 061026)
Answer with Explanation: https://www.clcoding.com/2026/10/python-coding-challenge-id-061026.html | 93 |
| 3 |  Writing Python code feels easy… until Python replies with a Traceback.
One missing variable, one tiny typo, and suddenly the whole plan changes!
100 Days of Math with Python
Learn mathematics by solving real problems with Python — from basic arithmetic and algebra to statistics, calculus, probability, and linear algebra.
100 Days • 100 Challenges • Math + Python
Projects: https://link.amazon/B05muC3HT | 125 |
| 4 |  Python Pattern Challenge — Day 20
Think you know Python loops and nested loops?
Today's pattern challenge is a simple way to test your understanding of:
Nested loops
range()
Pattern logic
Rows and columns
Problem-solving skills
Can you predict the output before running the code?
Try it yourself, then check the solution.
Day 20 is here: https://www.clcoding.com/2026/10/python-pattern-challenge-day-20.html | 133 |
| 5 |  SHAP makes machine learning models easier to understand.
Instead of just getting a prediction, you can see why the model made that prediction and which features pushed the result higher or lower.
In this example, a Random Forest model predicts a value from the California housing dataset, while a SHAP waterfall plot breaks down the individual contribution of each feature.
For example:
- AveOccup pushes the prediction down
- MedInc pushes it up
- Other features such as Longitude, Latitude, Population, and HouseAge also influence the final prediction
This is the power of Explainable AI (XAI) — moving from “What did the model predict?” to “Why did the model predict it?”
Projects: https://link.amazon/B03Rr0s1k | 146 |
| 6 |  Understanding Machine Learning: From Theory to Algorithms — Free PDF
Looking to build a strong foundation in Machine Learning?
This 449-page book takes you beyond simply calling ML libraries and focuses on the theory, concepts, and algorithms behind machine learning.
You’ll explore topics such as:
Machine Learning fundamentals
Supervised & unsupervised learning
Classification & regression
Learning algorithms
Generalization and model evaluation
Theoretical foundations of ML
Mathematical concepts behind algorithms
A valuable resource for students, Python developers, aspiring data scientists, and ML enthusiasts who want to understand how Machine Learning actually works.
449 pages of Machine Learning knowledge — available as a free PDF.
Get it here: https://www.clcoding.com/2026/07/understanding-machine-learning-from.html | 148 |
| 7 |  Prime deals are live, and if you're a developer, this can be a good opportunity to upgrade your workspace, coding setup, and everyday tech accessories.
You don't need to buy everything just because it's discounted. Instead, focus on products that can genuinely improve your productivity, comfort, and workflow.
Here are 10 products worth checking out.
https://x.com/clcoding/status/2107187656824361233?s=20 | 239 |
| 8 |  Did You Know?
Python Has a Special Interactive Shell
Python comes with an interactive shell (REPL) that lets you execute Python statements instantly—without creating a .py file.
Python is transforming the way we work with maps, geospatial data, and spatial analysis.
With Python, you can:
Analyze and visualize geospatial data
Work with Shapefiles, GeoJSON, and raster data
Create interactive maps
Perform spatial joins and geoprocessing
Analyze satellite and remote-sensing data
Automate GIS workflows
Build location-based applications
Work with coordinates, projections, and spatial databases
Projects: https://link.amazon/B0f4Cqywq | 148 |
| 9 |  🚀 October Python Bootcamp — Day 1 is here!
We’re starting from the ground up with Python Fundamentals.
In Day 1, we’ll cover:
- What is Python?
- Python installation & Jupyter Notebook
- Syntax and indentation
- Variables and naming conventions
- Comments
- print() and input()
- Basic coding exercises
Whether you're completely new to Python or want to strengthen your fundamentals, this session is a great place to start.
Join the live session for FREE and start your Python journey this October.
https://youtube.com/live/VSntnv4yT9U
Let’s learn Python by coding, practicing, and building step by step. | 168 |
| 10 |  Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 051026)
Answer with Explanation: https://www.clcoding.com/2026/10/python-coding-challenge-id-051026.html | 156 |
| 11 |  Python Coding Challenge — Day 1274
What is the output of the following Python code?
A small piece of Python code can sometimes produce a surprisingly tricky result.
Before running the code, take a moment to:
Read it carefully
Predict the output
Understand why Python behaves that way
Don’t just guess the answer — explain the reasoning behind it.
Think you know the output?
Check the full challenge here: https://www.clcoding.com/2026/10/python-coding-challenge-day-1274-what.html
Comment your answer before checking the solution. | 188 |
| 12 |  Rich Syntax makes Python code look better
If you work with Python in the terminal, Rich can make your output much more readable and visually appealing.
With rich.syntax, you can:
- Highlight Python code with syntax coloring
- Choose different themes such as monokai
- Display code directly in the terminal
- Make debugging and demos easier to read
https://link.amazon/B0exoJjOq | 176 |
| 13 |  FREE PYTHON BOOK ALERT
Want to make Python do the boring work for you?
“Automate the Boring Stuff with Python — 3rd Edition” is now available as a FREE PDF.
Learn how to:
- Automate repetitive tasks
- Work with Excel, CSV and PDF files
- Send emails automatically
- Scrape websites
- Organize files with Python
- Save hours of manual work
Less manual work. More automation. More Python.
Perfect for beginners and experienced developers who want to build practical automation skills.
Download your free copy and start automating your everyday tasks with Python today.
https://www.clcoding.com/2025/10/automate-boring-stuff-with-python-3rd.html | 185 |
| 14 | Why is Python losing ground in the latest TIOBE Index? Is this a temporary trend?
Read here: https://x.com/grok/status/2106821954472755372?s=20 | 205 |
| 15 |  Big Data and AI Strategies: Machine Learning and Alternative Data Approach to Investing
Want to explore how Big Data, Artificial Intelligence, Machine Learning, and alternative data are transforming modern investing?
This 280-page book explores how data-driven techniques can be applied to investment research, financial analysis, and decision-making.
What you’ll explore:
• Big Data in finance
• AI & Machine Learning for investing
• Alternative data sources
• Data-driven investment strategies
• Machine learning applications in financial markets
• The future of AI-powered investing
Free PDF: https://www.clcoding.com/2026/08/big-data-and-ai-strategies-machine.html | 245 |
| 16 |  Python Quiz of the Day
Python Coding Challenge - Question with Answer (ID 041026)
Answer with Explanation: https://www.clcoding.com/2026/10/python-coding-challenge-id-041026.html | 208 |
| 17 |  Python + Generative Art = Creative Coding!
Who said Python is only for data science and automation?
With just a few lines of Python, you can create generative artwork and turn it into a PDF.
This example uses PyMuPDF (fitz) + random to:
Generate 100 random circles
Create a unique visual pattern
Draw everything directly into a PDF
Add custom Python-themed text
Save the final artwork as a PDF
The best part? Every run can create a different design because the positions and sizes are randomized.
Python isn't just about solving problems —
it's also a tool for creativity.
https://link.amazon/B08YMfC6u | 217 |
| 18 |  Python Pattern Challenge — Day 19
Think you’re good at Python loops?
This pattern challenge might make you think twice!
Your challenge:
Can you predict the pattern and write the Python code to generate it?
Don’t just look at the output — understand the logic behind the pattern.
Practice:
• for loops
• Nested loops
• range()
• Pattern logic
• Problem-solving skills
Day 19 of the Python Pattern Challenge is here!
👉 Try it yourself before checking the solution:
https://www.clcoding.com/2026/10/python-pattern-challenge-day-19.html | 209 |
| 19 |  📊 Make Your Python Data Interactive!
Want to turn a Pandas DataFrame into an interactive visualization with just a few lines of code?
Meet HoloViews + hvPlot — a powerful combination for creating interactive charts without writing complex plotting code.
✨ Why hvPlot?
Interactive charts with minimal code
Works naturally with Pandas
Zoom, pan, hover & explore your data
Great for dashboards and data exploration
Built on the HoloViz ecosystem
Instead of static charts, let your data become interactive.
https://link.amazon/B0chJmgkp | 173 |
| 20 | Deep Learning Methods of Mathematical Physics — Volume I
Interested in the intersection of Deep Learning, Mathematics, and Physics? This 461-page resource explores how modern deep learning techniques can be applied to direct and inverse problems in mathematical physics.
🔹 Deep Learning & Mathematical Physics
🔹 Direct & Inverse Problems
🔹 Mathematical modeling
🔹 Scientific computing
🔹 Physics-informed approaches
🔹 461 pages of learning material
A useful resource for students, researchers, data scientists, and anyone exploring AI + Mathematics + Physics.
Free PDF: https://www.clcoding.com/2026/07/deep-learning-methods-of-mathematical.html | 185 |
