#java#cloud_native#hacktoberfest#java#kubernetes#reactive
Quarkus is a Java framework designed for cloud-native and container-first applications, making Java apps start up much faster and use less memory, which lowers cloud costs. It supports both traditional and reactive programming styles in one framework, so you can develop efficiently without learning new tools. Quarkus uses build-time processing and can compile to native images for even better performance. It integrates popular Java standards and libraries, making development smoother and more enjoyable. This means you can build modern, fast, and cost-effective Java applications easily, especially for Kubernetes and cloud environments[1][2][4][5].
https://github.com/quarkusio/quarkus
Amalgam company has released a miniature copy of 🚘12Cilindri for the price of Nissan Versa
🏎 The copy of Ferrari 12Cilindri is made in 1:8 scale (length about 60 centimeters). Amalgam designers achieve a high similarity with the original by using the original documentation and the help of the manufacturer's engineers.
📸 The attention to detail is astounding. The miniature leather interior is decorated with red contrast stitching, just like the full-size car. The level of accuracy is so high that the model can be mistaken for the real thing in the photos.
⏳ Each car takes about 300 hours to assemble by hand. In total, Amalgam will produce 119 coupe models and the same number of roadsters.
👍 As for the real Ferrari 12Cilindri, this car replaces the 812 Superfast, continuing the tradition of V12-powered grand tourers.
💸 The price of the model starts at $18,220.
@CarsNews
#Ferrari#sportscar#models
🌿 Xalqaro amaliy seminar: “Yashil” kelajak sari modellar va nazarlar
“Yangi O‘zbekiston” universiteti HTWD Dresden (Germaniya), Myunxen texnika universiteti (Germaniya) va Nemis-Iordan (Iordaniya)universitetlaribilan hamkorlikda ikki kunlik xalqaro seminar tashkil etmoqda.
Seminar-treyningda O‘zsanoatqurilishbank, Osiyo taraqqiyot banki va IT Park dan mutaxassislar va ekspertlar ishtirok etishadi.
📅 Sana: 2025-yil 5–6-noyabr
📍 Manzil: “Yangi O‘zbekiston” universiteti
Seminar dasturi 5-noyabr kuni asosiy ma’ruzalar va panel muhokamasidan boshlanadi:
❕“Yashil biznes modellari va mas’uliyatli innovatsiyalar: global va mahalliy istiqbollar”.
6-noyabr kuni TUM International amaliy seminar o‘tkazadi:
💡“Ta’limdan harakatga: barqarorlik va tadbirkorlik ta’siri uchun ta’lim berish”.
‼️Ro‘yxatdan o‘tish 4-noyabrgacha davom etadi.
👉Seminarga ro‘yxatdan o‘tish
🔁English
➖➖➖➖➖➖➖➖➖➖
#workshop#greenfuture#models
⬇️Biz ijtimoiy tarmoqlarda:
Veb-sayt | Telegram | Instagram | Facebook
http://deeplearning.net/software/theano/tutorial/index.html#basics
In terms of #algorithm availability, you can get plenty of algorithms out of the box with scikit-learn. And if you want to customize every detail of your #models, #Python has #Theano. In addition, Theano is easily configured to run on the #GPU, which gives you a cheap and easy way to get much higher speeds without having to change a single line of code or delve into performance details.
#вакансия#middle#senior#python#dev#postgresql#ml#math#models#sql
Всем привет!
Мы Axenix (ex. Accenture) находимся в поисках Python Developer на проект разработки продукта In.Plan (платформа интегрированного планирования)
🔎 Мы ищем Middle/Senior Python Developer
Формат работы: гибрид, удаленка (РФ/Армения/Казахстан)
💰 обсуждается после тех. интервью
Чем предстоит заниматься:
🔸 Разработка решений для платформы интегрированного планирования производства
🔸 Участие в написании модулей прогнозирования спроса, календарного планирования и производственного планирования, модуля оптимизации складских запасов
🔸 Работа с PostgreSQL как источником данных. Задачи включают написание компонентов по чтению/записи данных из БД, обработке (очистка, проверка качества, сглаживание и т.д.) данных, формулировке задач мат. оптимизации для солверов, написание ML модулей для прогнозирования.
Здорово, если ты:
🔹 Знаешь алгоритмы и структуры данных
🔹 Имеешь опыт коммерческой разработки на Python
🔹 Понимаешь и применял нотации Big O для оценки сложности алгоритмов
🔹 Знаешь паттерны ООП и принципы проектирования вычислительных решений
🔹 Имеешь опыт написания тестов, понимание отличий и целей разных типов тестов
🔹 Имеешь опыт работы с SQL базами данных
🔹 Знаешь Git
Мы предлагаем:
▪️ Работу в Аккредитованной ИТ-компании
▪️ Конкурентоспособный уровень дохода, годовые бонусы и регулярное повышение по результатам Performance Review
▪️ Культуру непрерывного обучения: сертификация, online и offline обучение в России, менторство в профессиональном развитии;
▪️ ДМС с первого месяца работы, включая стоматологию, в лучших клиниках Москвы и МО для cотрудника и его семьи (жена/муж, дети до 18 лет);
▪️ Возможность оформления по ИП
Контакт для связи: @masha_axenix
✨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 😊