— machine learning progress log: ⤷ numpy broadcasting practice ⤷ some numpy tricks and operations

The book “#AlgorithmicTrading with Python” discusses modern quant trading methods in #Python with a heavy focus on PANDAS, Numpy, and scikit-learn. Get it at: https://t.co/9LJFLrkh8t by @__chrisconlan__ + ➡️ Get free code from the book here: https://t.co/7o5hAjEbd3

Become an AI Engineer Core Skills You’ll Need: 1️⃣ Python — The foundation of AI. Learn data structures, OOPs, and libraries like NumPy, Pandas, and Scikit-learn. 2️⃣ Machine Learning — Master algorithms, feature engineering, and model deployment with Streamlit or Flask. 3️⃣ Deep

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"I used to feel guilty in Cambridge that I spent all day playing games, while I was supposed to be doing mathematics. Then I realized that playing games is math." John H. Conway Made with #python #numpy #matplotlib

Started learning Python libraries - beginning with NumPy 💻

🚀 Just started my #DataScience journey with #CodeWithHarry! Diving into Python, Pandas, NumPy & real-world ML projects 💻 Ready to turn data into decisions 🔥 #Python #MachineLearning #AI #CodeWithHarry #technology

Python tip: you can speed up your app by replacing import numpy as np with from numpy import *. This way, the interpreter skips a lookup per new function call

これ無料でいいの？ 千葉大がPython講義資料を公開してる テキストコピーのショートカットから始まって、 ・関数やクラスなどの基礎 ・numpy / scipy / matplotlib まで実践的に解説 Pythonを体系的に学びたい人、これ見逃すのもったいない

Learning how to vectorise numpy arrays properly holy shit man - I didn't realise it was so OP

Playing around with Odin simd, Python's ctpyes.Strutcure, and NumPy arrays. it is so fun ngl.

The ONLY Python Cheat Sheet You’ll Ever Need! 🔥 If you’re in Data Science, mastering Python (especially NumPy + Pandas) is a MUST. I made this all-in-one cheat sheet to save you from constantly Googling! 📚🔍 ✅ NumPy basics & array tricks ✅ Pandas DataFrame slicing &

📚 INDICAÇÃO DE LIVRO: Guia Do Python Para Data Science - Ferramentas Essenciais para Trabalhar com Dados - Jake VanderPlas O livro explica, de forma prática, como usar bibliotecas como NumPy, Pandas, Matplotlib e Scikit-Learn para explorar, visualizar e modelar dados.

The Bak-Sneppen model: species in a circle, each with random fitness. Replace the weakest species (and its neighbors) with new random values. Cascading evolutionary avalanches emerge, showing self-organized criticality from simple rules. Made with #python #numpy #matplotlib

Python for Data Analysis Book for FREE! Python for Data Analysis by Wes McKinney is a great book to learn Data wrangling with Pandas and Numpy. - 3rd Edition - Source Code - PDF version Follow me @python_spaces for more books. All for FREE! Find the book link in 🧵👇

🎬 Day 45 of #100DaysOfCode Excited to share that my Movie Recommendation System project is finally complete! I learned how to use Python, Pandas, NumPy, and Flask to build a system that suggests movies based on similarity. It was an amazing learning journey! 🚀

Python devs in 2025 really out here writing: "import pandas as pd" "import numpy as np" "import matplotlib" "import seaborn" "import sklearn" Then wondering why their 10-line script takes 8 seconds to start. "But Python is so easy and readable!" Yeah, until you hit: -

NumPy-based toolkit for sequence analysis, structure bioinformatics, database queries, and external tool integration in Python

Check out our first ML-Ops question! Sure, you could solve it easily with pandas… but where’s the fun in that? NumPy is all you need!