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Изворен канал @pythonmathaug22 · Post #33 · 19 сеп.

❗️ВАЖНО❗️ 🎾Обратная связь по четвертой неделе интенсива Оставить отзыв на занятия прошлой недели 12 и 15 сентября можно по ссылке: https://forms.gle/HCXZb1B8q77FoGDy8 🎾Обновления в домашних заданиях В домашней работе №3: – исправили ответы на вопросы №2 и №7 – добавили дополнительные 2 попытки, чтобы вы могли снова выполнить откорректированный тест (итого 5 разрешенных попыток) – продлили дедлайн до 24 сентября 23:59 (мск) В домашней работе №4: – поправили прием ответа на вопрос №12 (ранее у некоторых студентов возникали трудности) – добавили дополнительные 2 попытки, чтобы вы могли снова выполнить откорректированный тест (итого 5 разрешенных попыток) – дедлайн остается тем же: 30 сентября 23:59 (мск) 🎾 У меня возникают разные вопросы по задачам — к кому обратиться? К хелперам в Discord-комьюнити: мы раздали роль helpers тем, кто готов помогать начинающим с нуля. Хелперы отображаются красным цветом. Создали 10 мини-групп с 2-3 хелперами в каждой. В ближайшее время начнем распределять по мини-группам студентов, которые оставили реакции под постом о наборе в мини-группы начинающих. Этот пост находится в последнем закрепленном сообщении на канале #python-и-математика: реакции все еще можно оставить, если вы хотите в мини-группу. Хорошей недели! Команда Mathshub

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djangoproject

@djangoproject · Post #454 · 03.10.2017 г., 15:43

https://engineering.instagram.com/web-service-efficiency-at-instagram-with-python-4976d078e366 Web Service Efficiency at Instagram with Python #Instagram currently features the world’s largest deployment of the #Django web framework, which is written entirely in #Python. We initially chose to use Python because of its reputation for simplicity and practicality, which aligns well with our philosophy of “do the simple thing first.” But simplicity can come with a tradeoff: efficiency...

Repositorio data science

@repo_science · Post #3533 · 23.08.2023 г., 16:42

#python#book#DataScience 📚 Encyclopedia of Data Science and Machine Learning Description Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. 📆2023 ⚖️155 MB 🔗Link ----- Main channel:@repo_science Coupons: @freecoupons_reposcience -----

Repositorio data science

@repo_science · Post #3268 · 06.06.2023 г., 00:41

#python#algorithms 🐍 Algorithmic Thinking with Python: Foundations Learn how to develop your algorithmic thinking skills to become a better problem solver. 🗣Robin Andrews 📆2022-04-26 ⌚️1h 11m 🔗Link ----- Main channel:@repo_science Coupons: @freecoupons_reposcience -----

Analytics and growth mindset ️

@thinkbroadly · Post #9 · 20.05.2024 г., 09:18

🔥 20 Step-by-Step Data Analysis Projects with Python Code Below are popular data analysis projects from Kaggle, Github, and Medium users. They will: - Help you gain skills in working with real data - Introduce you to Python libraries for data analysis - Inspire you for your own data analysis projects #data_analyst#data_analysis#data_projects ☕Coffee Shop Sales Analysis ⚽ FIFA World Cup Data Analysis ⚡️ADIDAS Sales Analysis 📱Netflix Data Analysis (1) ⚡️ Zomato Data Analysis 🍫 Product Sales Analysis 🚕 Uber Rides Data Analysis 👀Smartwatch Data Analysis 🤑Financial Budget Analysis 📱Netflix Data Analysis (2) 🎮 Video Game Sales Analysis 🤓 Is There a Trend of Increasing Geek Girls? 🏆 Let's Discover More About the Olympic Games! 📉Marketing Analysis 🐶Animal Shelter Data Analysis 📱 Amazon Data Analysis 💲Billionaire Data Analysis 📱 Credit Card Data Analysis 😏Pokemon Data Analysis 📱Spotify Data Analysis. What Does It Take to Hit the Charts #DataAnalyst#DataAnalytics#DataAnalysis#data_analyst#python If you find this content useful, give it a🔥!

GitHub Trends

@githubtrending · Post #15386 · 03.01.2026 г., 11:30

#python#beancount Beancount is free, open-source double-entry accounting software that uses simple text files to track finances, create reports, and view data via a web interface. Download the current stable Version 3 from GitHub, check docs at beancount.github.io/docs, and ask questions on the mailing list. This helps you manage money flexibly with version control, automation, privacy, and no vendor lock-in, saving time on tracking expenses, assets, and budgets accurately. https://github.com/beancount/beancount

GitHub Trends

@githubtrending · Post #15161 · 21.09.2025 г., 12:30

#python#ai_researcher AI-Researcher is a powerful tool that fully automates scientific research from start to finish. It can review literature, generate new research ideas, design and implement algorithms, validate results, and even write complete academic papers. You just provide research ideas or reference papers, and it handles the rest using advanced AI agents. This saves you time and effort by streamlining complex research tasks, helping you innovate faster without needing deep technical expertise. It supports multiple AI models, offers a user-friendly web interface, and includes a benchmark to evaluate research quality, making it an efficient assistant for accelerating scientific discovery. https://github.com/HKUDS/AI-Researcher

djangoproject

@djangoproject · Post #540 · 28.12.2017 г., 12:26

https://github.com/google/python-fire #Python#Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object. Python Fire is a simple way to create a CLI in Python. Python Fire is a helpful tool for developing and debugging Python code. Python Fire helps with exploring existing code or turning other people's code into a CLI. Python Fire makes transitioning between Bash and Python easier. Python Fire makes using a Python REPL easier by setting up the REPL with the modules and variables you'll need already imported and created.

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