📝❗️В сентябре прошлого года YouTube удалил два новостных канала RT (RT DE и Der Fehlende Part) без возможности восстановления из-за нарушения условий пользовательского соглашения. В декабре YouTube снова удалил запущенный для немецкого вещания канал RT auf Sendung, также аргументируя это нарушениями правил видеохостинга. Представители правительства ФРГ отрицают свою причастность к блокировкам RT на территории их страны.
Однако, учитывая тот факт, что YouTube, вероятно, является монопольным поставщиком услуг видеохостинга в ЕС в свете практически отсутствующей конкуренции, не являются ли меры в отношении новостных каналов RT нарушением положений ГАТС?
#торговыйпереговорщик#ВТО#ГАТС#YouTube#RT#ЕС
🤔British & American kids would much rather be YouTubers than astronauts!
Last week, we had the 50th Apollo 11 anniversary, which landed Neil Armstrong and Buzz Aldrin on the surface of the Moon. On the eve of that, LEGO asked The Harris Poll to survey a total of 3,000 children in 🇺🇸🇬🇧🇨🇳 about their attitudes toward and knowledge of space.
Asked what they would like to be when they grow up, about 3 in 10 American and British children replied that they wanted to be YouTubers or Vloggers. In fact, becoming an astronaut ranked last among five professions! Only in China did children have a clear preference for being an astronaut!
#️⃣#SocialMedia#Influencers#YouTube#NASA
📡 from arsTechnica via Pulse.
🦅@PerspectiveIX
❓How will this affect the West in 50 years?
✨The STAR method is a powerful technique used to answer behavioral interview questions effectively.
It helps structure responses by focusing on Situation, Task, Action, and Result. For analytics professionals, using the STAR method ensures that you demonstrate your problem-solving abilities, technical skills, and business acumen in a clear and concise way.
Here’s how the STAR method works, tailored for an analytics interview:
📍 1. Situation
Describe the context or challenge you faced. For analysts, this might be related to data challenges, business processes, or system inefficiencies. Be specific about the setting, whether it was a project, a recurring task, or a special initiative.
Example: “At my previous role as a data analyst at XYZ Company, we were experiencing a high churn rate among our subscription customers. This was a critical issue because it directly impacted revenue.”*
📍 2. Task
Explain the responsibilities you had or the goals you needed to achieve in that situation. In analytics, this usually revolves around diagnosing the problem, designing experiments, or conducting data analysis.
Example: “I was tasked with identifying the factors contributing to customer churn and providing actionable insights to the marketing team to help them improve retention.”*
📍 3. Action
Detail the specific actions you took to address the problem. Be sure to mention any tools, software, or methodologies you used (e.g., SQL, Python, data #visualization tools, #statistical#models). This is your opportunity to showcase your technical expertise and approach to problem-solving.
Example: “I collected and analyzed customer data using #SQL to extract key trends. I then used #Python for data cleaning and statistical analysis, focusing on engagement metrics, product usage patterns, and customer feedback. I also collaborated with the marketing and product teams to understand business priorities.”*
📍 4. Result
Highlight the outcome of your actions, especially any measurable impact. Quantify your results if possible, as this demonstrates your effectiveness as an analyst. Show how your analysis directly influenced business decisions or outcomes.
Example: “As a result of my analysis, we discovered that customers were disengaging due to a lack of certain product features. My insights led to a targeted marketing campaign and product improvements, reducing churn by 15% over the next quarter.”*
Example STAR Answer for an Analytics Interview Question:
Question: *"Tell me about a time you used data to solve a business problem."*
Answer (STAR format):
🔻*S*: “At my previous company, our sales team was struggling with inconsistent performance, and management wasn’t sure which factors were driving the variance.”
🔻*T*: “I was assigned the task of conducting a detailed analysis to identify key drivers of sales performance and propose data-driven recommendations.”
🔻*A*: “I began by collecting sales data over the past year and segmented it by region, product line, and sales representative. I then used Python for #statistical#analysis and developed a regression model to determine the key factors influencing sales outcomes. I also visualized the data using #Tableau to present the findings to non-technical stakeholders.”
🔻*R*: “The analysis revealed that product mix and regional seasonality were significant contributors to the variability. Based on my findings, the company adjusted their sales strategy, leading to a 20% increase in sales efficiency in the next quarter.”
Hope this helps you 😊
#вакансия#python#cv#ml#fulltime#remote#удалённо#datascience
Python-разработчик (Computer Vision)
от 200 000 до 300 000 ₽ на руки
Требуемый опыт работы: 3–6 лет
Полная занятость, полный день
Мы в Megainsight разрабатываем коробочную систему рекомендаций на основе видеопотоков в реальном времени с различными алгоритмами обнаружения и распознавания для анализа автомобилей, людей и очередей в розничной торговле. Это продуктовое решение.
- Вам необходимо быстро погрузиться в текущий этап проекта системы видеоаналитики и взяться за реализацию блока бизнес-логики – обработки и синхронизации событий на основе видеоданных;
- Мы ожидаем от кандидата решения задач по интеграции бизнес-логики с блоком компьютерного зрения;
- Осуществлять проектирование и внедрение сервисов, их взаимодействие;
- Проектирование архитектуры и серверной реализации решения;
Требования:
- Язык программирования – Python;
- Опыт написания кода в коммерческой среде;
- Опыт межсервисного взаимодействия, знание механизмов синхронизации;
- Опыт работы с реляционными хранилищами данных (PostgreSQL, ClickHouse);
- Опыт работы с Linux, Docker и Git/Gitlab;
- Английский – чтение технической литературы и научных статей;
- Способность прогнозировать и балансировать долгосрочное стратегическое проектирование и краткосрочные тактические решения;
- Самоорганизованность и инициативность, опыт оформления проведенных экспериментов и результатов работы.
Будет преимуществом:
- Знакомство с фреймворками для задач компьютерного зрения: Pytorch/Keras/Tensorflow, OpenCV;
- Реализация проектов Computer Vision от сбора данных до внедрения в производство;
Перспективы и возможности:
- Наша компания активно развивает глобальное направления в Европе, Латинской Америке и на Ближнем Востоке. Это возможность для вас получить международный проектный опыт.
- Есть возможность релокации и работы в других странах.
- Работа предполагает удаленный формат, при этом мы гарантируем полное оформление в соответветствии с трудовым законодательсвом страны нахождения.
Контакты: Дмитрий Брунеткин, [email protected]
#webScraping#Python#Scrapy
🐍
Scrapy course - Python web scraping for beginners
The Scrapy #Beginners Course will teach you everything you need to learn to start scraping websites at scale using #Python Scrapy.
Topics
- Creating your first #Scrapy spider
- #Crawling through websites & scraping data from each page
- Cleaning data with Items & Item Pipelines
- Saving data to CSV files, #MySQL & #Postgres#databases
- Using fake #user-agents & headers to avoid getting blocked
- Using #proxies to scale up your web scraping without getting banned
- Deploying your #scraper to the cloud & scheduling it to run periodically
🗣️ Joe Kearney.
🔗Link
📢#youtube
⭐️ Resources ⭐️
Course Resources
- Scrapy Docs
- Course Guide
- Course Github
- The Python Scrapy Playbook
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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#python#llms#mlx
MLX LM is a Python tool that helps you run and fine-tune large language models (LLMs) efficiently on Apple Silicon Macs. It connects easily to thousands of models on Hugging Face, supports model quantization to save memory, and allows distributed training. You can generate text or chat with models via simple commands or Python code. It also offers features like prompt caching and memory optimization for handling long texts, making it faster and less resource-heavy. This means you can run powerful AI models locally on your Mac without needing expensive cloud services, saving cost and improving speed.
https://github.com/ml-explore/mlx-lm
Il mio proposito 2025: si comincia da Trieste, Bologna, Cadelbosco e altri spettacoli di gennaio! 🤩
E buona fine di 2024 a tutti voi!
#rickdufer#dailycogito#filosofia#cogitostudios#youtube#teatro
https://youtube.com/shorts/HWQP9l6s-7o?feature=share
#Python#dataScience#aporte
🐍
The Data Science Course: Complete data science 2023
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Main channel: @repo_science
Coupons: @freecoupons_reposcience
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