140+ Python Practice Programs - For Real Learning, Not Just Theory
Struggling with Python logic?
Here's over 140 real Python programs that will help you to understand how code actually works-beyond the tutorials.
From basics to interview-level logic:
Arithmetic & conversions
Loops, Recursion, Lists, Arrays
Prime, Fibonacci, Armstrong logic
Matrices, Sorting, Factorials & more
Python pdf
Struggling with Python logic?
Here's over 140 real Python programs that will help you to understand how code actually works-beyond the tutorials.
From basics to interview-level logic:
Arithmetic & conversions
Loops, Recursion, Lists, Arrays
Prime, Fibonacci, Armstrong logic
Matrices, Sorting, Factorials & more
Python pdf
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🚀 Free & Relevant Books for Data Science (2025) 📚
Want to sharpen your Python & DS skills without outdated material? Here are some modern, still-relevant free books 👇
1️⃣ Python Data Science Handbook – Jake VanderPlas
🔗 https://jakevdp.github.io/PythonDataScienceHandbook
Core libs: NumPy, Pandas, Matplotlib, Scikit-Learn. Updated + interactive notebooks.
2️⃣ Python for Data Analysis (3rd Ed.) – Wes McKinney
🔗 https://github.com/wesm/pydata-book
By the creator of Pandas. Modern data wrangling & cleaning.
3️⃣ Dive into Deep Learning (D2L.ai)
🔗 https://d2l.ai
Hands-on deep learning with PyTorch & TensorFlow. University-level, interactive.
4️⃣ Minimalist Data Wrangling with Python (2023) – Marek Gagolewski
🔗 https://arxiv.org/abs/2211.04630
Practical workflows for real-world messy data.
5️⃣ Machine Learning with PyTorch & Scikit-Learn – Raschka et al.
🔗 https://github.com/rasbt/machine-learning-book
End-to-end ML with clean, modern Python code.
✨ Start with VanderPlas & McKinney for core skills, then move to Raschka/D2L for ML.
Want to sharpen your Python & DS skills without outdated material? Here are some modern, still-relevant free books 👇
1️⃣ Python Data Science Handbook – Jake VanderPlas
🔗 https://jakevdp.github.io/PythonDataScienceHandbook
Core libs: NumPy, Pandas, Matplotlib, Scikit-Learn. Updated + interactive notebooks.
2️⃣ Python for Data Analysis (3rd Ed.) – Wes McKinney
🔗 https://github.com/wesm/pydata-book
By the creator of Pandas. Modern data wrangling & cleaning.
3️⃣ Dive into Deep Learning (D2L.ai)
🔗 https://d2l.ai
Hands-on deep learning with PyTorch & TensorFlow. University-level, interactive.
4️⃣ Minimalist Data Wrangling with Python (2023) – Marek Gagolewski
🔗 https://arxiv.org/abs/2211.04630
Practical workflows for real-world messy data.
5️⃣ Machine Learning with PyTorch & Scikit-Learn – Raschka et al.
🔗 https://github.com/rasbt/machine-learning-book
End-to-end ML with clean, modern Python code.
✨ Start with VanderPlas & McKinney for core skills, then move to Raschka/D2L for ML.
jakevdp.github.io
Python Data Science Handbook | Python Data Science Handbook
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Remove Backgrounds from Images Using Python - No Manual Editing Needed
If you've ever spent time manually removing image backgrounds, there's a smarter way to do it - all thanks to Python.
Using the rembg library, it's now possible to remove image backgrounds automatically with just a few lines of code. Whether you're dealing with product photos, profile pictures, or building computer vision projects, this tool can save hours of effort
If you've ever spent time manually removing image backgrounds, there's a smarter way to do it - all thanks to Python.
Using the rembg library, it's now possible to remove image backgrounds automatically with just a few lines of code. Whether you're dealing with product photos, profile pictures, or building computer vision projects, this tool can save hours of effort
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