12 Minutes to Learn NumPy (Python): Arrays, Reshape, Arange & Linspace скачать в хорошем качестве

12 Minutes to Learn NumPy (Python): Arrays, Reshape, Arange & Linspace

👉 Join my Python Masterclass ~ https://www.zerotoknowing.com/join-now ***Save 20% off your First Month with code: save20now 12 Minutes to Learn NumPy (Python): Arrays, Reshape, Arange & Linspace — Learn the essentials FAST. NumPy array basics, reshape examples, arange vs linspace, random sampling and matrix tips — all in one compact Python crash course. 👉 Join our Discord Community ~   / discord   👉 Join my Python Newsletter ~ https://www.thenerdnook.io 📚 Read my eBooks ~ https://www.zerotoknowing.com/ebooks What is NumPy? NumPy (Numerical Python) is the foundational Python library for fast numeric arrays and vectorized math — the go-to toolkit for data science, ML, and scientific computing. Learn the core functions you’ll actually use on real projects. NumPy In this numpy tutorial you'll get: • Hands-on NumPy array creation and indexing (np.array, np.arange, np.linspace). • How and when to use np.reshape to change array shapes (with live examples). • np.arange vs np.linspace — choose the right range function and avoid common pitfalls. • Using np.random for sampling, seeds, and test data. • Quick look at NumPy matrices, broadcasting, and common pitfalls new Python users face. 👉 Get my Masterclass ~ https://www.zerotoknowing.com/join-now 📘 Join our Facebook ~ https://tinyurl.com/msy8mnxm Subscribe for content that helps you grow! 💥 PARTNER WITH ME - https://www.passionfroot.me/code-with... MY FAVORITE BOOKS 🐍 Python Crash Course - https://amzn.to/3vGDXqH 🛺 Automate the boring stuff - https://amzn.to/428yoO0 💽 Data Structures and Algorithms in Python - https://amzn.to/3SkzYZL 📘 Python pocket reference - https://amzn.to/3SlK0tA PS: Some of the links in this description are affiliate links that I get a kickback from 😜 🎬 Timestamps: 0:00 | Intro / What is NumPy? (NumPy Python Basics for Beginners) 0:25 | Why Use NumPy in Python (Speed vs Python Lists) 1:20 | Create Arrays in NumPy: np.array, np.arange, np.linspace Explained 3:53 | NumPy Reshape Examples: np.reshape 1D, 2D, and 3D Arrays 6:30 | Indexing and Slicing NumPy Arrays (Beginner Tutorial) 8:30 | NumPy Mathematical Operations with Arrays 9:30 | NumPy Statistical Operations: np.mean, np.std Examples 10:55 | Boolean Indexing with NumPy Arrays 12:25 | Simple NumPy Broadcasting Explained 13:52 | NumPy Random Module: np.random, np.seed, np.randint 15:00 | Array Concatenation in NumPy (Join Multiple Arrays) 16:16 | Next Steps & NumPy Resources 🔹🔹🔹🔹🔹🔹🔹🔹🔹 🎙 PyPod Chronicles - https://thenerdnook.substack.com/podcast 🗞 LinkedIn -   / josh-wenner   👨‍💻 GitHub - https://github.com/Joshwen7947 🔹🔹🔹🔹🔹🔹🔹🔹🔹 Tag ~ zero to knowing, code with josh #numpy #pythontutorial #numpyarrays #learnpython #datascience