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Хоумстейджинг с любовью ❤️ / Homestaging / ПИК Гранель Инград Самолет
@hswithlove
1.6K

Евро2 для сдачи в аренду со сметой на покупки 870тыс - показываем, что получилось 👌

ЖК «Скандинавия» (А101) Площадь - 34м² Ремонт от застройщика. Постоянный заказчик обратился к нам за комплектацией двух одинаковых квартир в этом ЖК Это квартира N2

А Квартира N1 - см. https://t.me/hswithlove/9280

В стоимость вошли: • кухня • мебель • техника • текстиль • декор • две мульти-сплит-системы

Главный дизайнер - Ирина Кураторы проекта - Екатерина, Евгения

Услуги нашей студии в этом проекте: • комплектация • хоумстейджинг • фотосессия

❓Какие артикулы и ссылки написать? О чем рассказать? Ответим в следующих постах на самые популярные вопросы (чем можем делиться ☺️) 🙌 Вопросы принимаем в течение 24 часов ⏰

🤍 ПРАЙС НА НАШИ УСЛУГИ 🤍 КАКОЙ БЮДЖЕТ НУЖЕН НА КОМПЛЕКТАЦИЮ

📲Телеграм 📲 MAX | 📱 ВК | 🌐 Сайт

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curiousprogrammer
@curiousprogrammer
433

🚀 Top 100 AI Interview Questions

🧠 AI Fundamentals

1. Can you explain what Artificial Intelligence is in simple terms? 2. What is the difference between Artificial Intelligence, Machine Learning, and Deep Learning? 3. What are the different types of AI? 4. Can you explain the difference between Narrow AI and General AI? 5. What are Intelligent Agents in AI? 6. How does an AI system make decisions? 7. What is heuristic search in AI? 8. What is the difference between Breadth-First Search and Depth-First Search? 9. Can you explain a real-world application of AI that you use daily? 10. Why is AI becoming important across industries?

📊 Machine Learning Basics

11. What is Machine Learning and how does it work? 12. What are the different types of Machine Learning? 13. What is the difference between supervised and unsupervised learning? 14. Can you explain reinforcement learning with a real-world example? 15. What is the difference between training data and testing data? 16. Why do we split data into train and test sets? 17. What is overfitting in Machine Learning? 18. What is underfitting and how can you detect it? 19. Can you explain the bias-variance tradeoff? 20. What is feature engineering and why is it important?

📈 Regression

21. What is Linear Regression and where is it used? 22. What assumptions does Linear Regression make? 23. What is multicollinearity and why is it a problem? 24. What is Ridge Regression? 25. What is Lasso Regression? 26. What is the difference between Ridge and Lasso Regression? 27. How do you evaluate a regression model? 28. What is RMSE and why is it important? 29. What does R² score tell you about a model? 30. When would you choose regression over classification?

🔍 Classification

31. What is a classification problem in Machine Learning? 32. What is the difference between Logistic Regression and Linear Regression? 33. How does a Decision Tree work? 34. What are the advantages of Random Forest? 35. What is Support Vector Machine (SVM)? 36. Why is Naive Bayes called “naive”? 37. How does the KNN algorithm work? 38. What is a confusion matrix? 39. What is the difference between precision and recall? 40. Why is F1-score important?

📉 Clustering & Unsupervised Learning

41. What is clustering in Machine Learning? 42. How does K-Means clustering work? 43. What is hierarchical clustering? 44. What is DBSCAN and when would you use it? 45. What is dimensionality reduction? 46. What is PCA and why is it used? 47. What is the difference between PCA and clustering? 48. What is anomaly detection? 49. Can you explain association rule learning with an example? 50. What are some real-world applications of clustering?

🧠 Deep Learning

51. What is Deep Learning and how is it different from Machine Learning? 52. What is a Neural Network? 53. Can you explain how a perceptron works? 54. What are activation functions and why are they needed? 55. Why is ReLU widely used in Deep Learning? 56. What is backpropagation in neural networks? 57. How does gradient descent optimize a model? 58. What is the vanishing gradient problem? 59. What is dropout in Deep Learning? 60. What is the difference between CNN and RNN?

💬 Natural Language Processing (NLP)

61. What is NLP and where is it used? 62. What is tokenization in NLP? 63. Why do we remove stopwords in text preprocessing? 64. What is stemming? 65. What is lemmatization and how is it different from stemming? 66. What is TF-IDF and why is it useful? 67. What are word embeddings? 68. Can you explain sentiment analysis with an example? 69. What are transformers in NLP? 70. What is a Large Language Model (LLM)?

👁️ Computer Vision

71. What is Computer Vision? 72. What is image classification? 73. What is object detection and how is it different from image classification? 74. How does a CNN process images? 75. What is pooling in CNN? 76. Why is image augmentation important? 77. What is transfer learning in Deep Learning?

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Generative AI
@generativeai_gpt
772

🚀 Generative AI Fundamentals – Part 2

🧠 Large Language Models (LLMs) Deep Dive

Understanding LLMs is one of the most important topics in GenAI interviews.

1. What is a Large Language Model (LLM)?

A Large Language Model (LLM) is a deep learning model trained on massive amounts of text data to understand, generate, summarize, translate, and reason about human language.

LLMs are built using the Transformer architecture and predict the next token based on the context of previous tokens.

Examples:

GPT

Llama

ChatGPT

Claude

Mistral

2. How are LLMs trained?

LLMs are typically trained in three stages:

Stage 1: Pretraining

The model learns language patterns from billions of words collected from books, websites, articles, and code.

The model learns:

Grammar

Facts

Reasoning patterns

Writing styles

Relationships between words

Stage 2: Fine-Tuning

The pretrained model is further trained on domain-specific data.

Examples:

Medical chatbot

Banking assistant

Legal assistant

Coding assistant

This makes the model specialized for particular tasks.

Stage 3: Alignment (RLHF)

The model learns from human feedback.

Goals:

Produce safer responses

Follow instructions better

Reduce harmful outputs

Improve helpfulness

3. How does an LLM generate text?

User Prompt

Tokenization

Embeddings

Transformer Layers

Attention Mechanism

Probability Distribution

Next Token Prediction

Repeat Until Complete

The model predicts one token at a time until the response is finished.

4. What are Tokens?

A token is the smallest unit processed by an LLM.

Example:

Sentence:

Artificial Intelligence is amazing.

Possible tokens:

Artificial

Intelligence

is

amazing

.

Some tokenizers split words into smaller subwords.

Example:

unbelievable

un

believ

able

5. What are Parameters?

Parameters are the learned weights inside a neural network.

They store everything the model learns during training.

Examples:

Small model → Millions of parameters

Large model → Billions of parameters

Generally:

More parameters → Better learning capacity

More parameters → Higher memory and compute requirements

6. What is Context Window?

The context window is the maximum amount of information (measured in tokens) the model can process in one request.

It includes:

User prompt

Previous conversation

Retrieved documents

System instructions

A larger context window helps with:

Long documents

Multi-turn conversations

Better RAG performance

7. What is Inference?

Inference is the process of using a trained model to generate predictions or responses.

Example:

Training → Teaching the model

Inference → Using the trained model to answer questions

Inference happens every time you interact with an AI chatbot.

8. What is Temperature?

Temperature controls the randomness of the generated response.

Low Temperature (0.1–0.3)

More deterministic

Better for factual tasks

Less creative

High Temperature (0.8–1.2)

More creative

More varied responses

Higher chance of unexpected outputs

9. What is Top-p Sampling?

Top-p (nucleus sampling) selects the next token from the smallest set of tokens whose cumulative probability exceeds a chosen threshold.

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whalepumpsreborn
@whalepumpsreborn
159

LONG SIGNAL | $MAV 1D BULLISH ( Swing trade ) 👑

Entry : 0.008 - 0.0081 Leverage : Cross 5x - 10x Target : 0.0115 - 0.013 Stoploss at : 0.007

Reason : $MAV is currently undervalued. The price has split 100 times from its all-time high. Recent dips have consistently been reabsorbed at 0.008. I've entered a small position here and will hold until it shows signs of a strong rebound ↗️

✉️Telegram 🐣Twitter ⚡️Boost

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eqstockidea
@eqstockidea
174

Inflation remains under control, while Flls have turned net buyers again in July 2026 after a prolonged selling phase and Dlls continue to provide strong support. If earnings growth and capital inflows continue, the current correction could lay the foundation for the next leg of the bull market.

India's mutual fund industry still has enormous growth potential. Total mutual fund AUM stands at Rs.82.22 lakh crore (~US$980 billion), with only around 4% of the population investing and mutual fund AUM equivalent to 25.4% of GDP. In comparison, the US mutual fund industry manages US$33.15 trillion, with 38% of the population investing and AUM equal to 137% of GDP, indicating significant long-term growth potential for India's mutual fund industry.

As per market grapevine, several blue-chip companies including Reliance, HDFC Bank, TCS, HUL, Infosys, ITC, ONGC, Nestlé and many others have delivered little or no returns over extended periods despite strong underlying businesses. The key takeaway is that investing in a good company alone is not enough. Proper entry and exit timing, along with regular technical and fundamental reviews, are equally important for generating superior returns.

Indian Stock Market: Leverage is the New Squid Game. Key takeaway: Nithin Kamath (Zerodha) and Andy Mukherjee (Bloomberg) have raised concerns over the rapid rise in leverage. India's MTF book has surged nearly 6x since 2023, with over 50% exposure in Non-F&O stocks, unlike Korea where leverage was largely concentrated in liquid large-cap stocks. India's MTF book has grown sharply: Mar 2023: Rs.25,000 crore, Mar 2025: Rs.68,000 crore, Jun 2025: Rs.85,000 crore, Aug 2025: Rs.96,000 crore, Oct 2025: Rs.1 lakh cror, Dec 2025: Rs.1.16 lakh crore, Jan 2026: Rs.1.16 lakh crore, Feb 2026: Rs.1.15 lakh crore (first monthly decline in one year), Mar 2026: Rs.1.06 lakh crore (Iran conflict, crude spike and Fll selling), Apr 2026: Rs.1.16 lakh crore, May 2026: Rs.1.27 lakh crore, Jun 2026: Rs.1.33 lakh crore, Jul 2026: Rs.1.44 lakh crore. Korea's market crash is a warning. Following massive leveraged losses, authorities introduced suicide prevention hotlines, Al bridge surveillance and enhanced psychiatric support, highlighting the devastating impact of excessive leverage. For retail investors, the lesson is simple: Avoid leverage, avoid margin trading and avoid excessive borrowing for stock investments. SEBI's June 2026 consultation paper highlighted that the MTF book is growing at nearly 50% YoY, reflecting rising leverage in the Indian market. Although India's MTF book is only 0.3% of total market capitalization versus 0.8% in South Korea, the quality of leverage is a bigger concern as 51% of MTF exposure is in Non-F&O small and mid-cap stocks, where liquidity is limited. Unlike Korea's Al-led bull market, India's leverage has built up during a largely sideways-to-weak market over the last two years. If leverage continues rising without a corresponding increase in market capitalization, it could become a significant risk for retail investors.

TGV SRAAC is expected to report strong Q1 results following robust performances by Gujarat Alkali and Lords Chloro. Promoters have purchased 4.77 lakh shares over the last two quarters, reflecting confidence in the company's prospects. The stock trades at a P/E of just 8, offers a 10% dividend yield, and appears attractive compared with its all-time high of Rs.182.

HFCL is emerging as a key beneficiary of the rising demand for fibre-optic drones, which are expected to require 70-100 million fibre kilo-metres of A2 fibre. As countries increasingly shift from radio-controlled drones to optical drones to prevent signal jamming, HFCL remains a stock to keep on the radar.

Paytm has launched the 'Split Bills' feature, enabling users to split and settle shared expenses directly through the app. The addition strengthens Paytm's digital payments ecosystem by integrating expense management with UPI-based settlements, enhancing user engagement.

Talbros Engineering has acquired a 40,000 sq. m. industrial premises at Pithampur, Madhya Pradesh, for Rs.25 crore to support future expansion and new projects. The development strengthens its long-term growth outlook, and the stock may surpass its 52-week high of Rs.766.

Rajesh Power has secured a Rs.70.05 crore order from Rajasthan Vidyut Prasaran Nigam, taking fresh order inflows over the last 30 days to more than Rs.1,003 crore. The company reported FY26 PAT of Rs.143 crore, EPS of Rs.80, ROCE of 48.6% and Q1 FY27 revenue of Rs.436.62 crore, while its unexecuted order book has grown to Rs.4,745 crore.. Supported by strong fundamentals, attractive valuations and expansion into Battery Energy Storage Systems (BESS), the stock looks attractive at the current market price compared with its 52-week high of Rs.1,639.

BMW Industries has reserves of Rs.781 crore against equity of Rs.22.51 crore, with promoters holding 74.36%. It reported 87% higher Q4FY26 PAT of Rs.33 crore and FY26 PAT of Rs.80.77 crore, while announcing a 43% dividend. Its Bokaro greenfield steel project is on track for commissioning in Q1FY27. The stock looks attractive at Rs.48 versus its lifetime high of Rs.86.

IRB Infrastructure reported 51.2% higher Q1FY27 PAT of Rs.306 crore. It expects 5-6% traffic growth, 22-25% toll revenue growth in FY27 and stronger ordering activity in H2FY27. Keep the stock on the radar.

Morepen Laboratories has reserves of Rs.1,137 crore against equity of Rs.110 crore and exports APIs to over 90 countries. Its API facility received USFDA clearance with NIL Form 483 and it secured a Rs.825 crore CDMO contract, with another Rs.225 crore expected in Q2FY27. The stock looks attractive at Rs.57 versus its lifetime high of Rs.222.

Talbros Engineering posted 80% higher Q4FY26 EPS of Rs.19 and FY26 EPS of Rs.57.4, while increasing its dividend to 30%. The company has expanded capacity through new facilities in Faridabad and Madhya Pradesh. Trading at just 12x PE against peers at 30x, the stock offers strong long-term potential.

TGV Sraac has reserves of Rs.1,190 crore against equity of Rs.28 crore and trades at just 0.85x book value. Promoters increased their stake to 64.26%. FY26 PAT rose 43% to Rs.132 crore with a 10% dividend. Ongoing Rs.220 crore capex and solar capacity expansion are expected to support FY27 earnings. The stock looks attractive at Rs.103 versus its all-time high of Rs.182.

Sathlokhar Synergys E&C Global reported a strong Q1FY27 performance with total income rising 67.8% YoY to Rs.206.19 crore, EBITDA surging 131.4% to Rs.31.35 crore, EBITDA margin expanding to 15.2%, and PAT jumping 132.6% to Rs.21.41 crore.

Cupid has strengthened its strategic partnership with GII Healthcare Investment through an additional USD 5 million investment, funded entirely through internal accruals.

Premium Plast has acquired an under-construction manufacturing facility in Bagroda Industrial Area, Bhopal, for Rs.99 lakh to support its future expansion plans.

Liotech Industries reported FY26 total income of Rs.70.50 crore (+73.3% YoY), EBITDA of Rs.10.40 crore (+58.2% YoY), and net profit of Rs.6.32 crore (+53.9% YoY). The company also secured a Rs.6.46 crore domestic order for architectural hardware products.

Patel Retail has expanded its retail footprint by opening its 53rd store at Uran, Raigad, further strengthening its presence across the Mumbai Metropolitan Region.

Neetu Yoshi secured Indian Railways orders worth Rs.20.11 crore, including a Rs.17.12 crore contract for axle box housings and related components, along with a Rs.2.99 crore order for centre pivot tops.

Vivid Electromech has strengthened its leadership team with the appointment of a new CFO and Company Secretary, bringing extensive expertise in strategic finance, fundraising, investor relations and corporate governance.

Emerald Finance has partnered with Vausm Technologies to launch its new Early Wage Access (EWA) programme in Punjab, expanding its fintech offerings.

S
subhrotech
@subhrotech
106

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🦊 BoxFox | КАНАЛ с акциями и скидками
@boxfoxx_katalog
24

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christinabelayaa
@christinabelayaa
201

Всё! Я все таки не выдержала и впервые сделала запуск уроков РАНЬШЕ, чем планировала

Ну Уран в 1 доме Лунара девчат, даже не спрашивайте почему и зачем 😂 Не знаююю

Выгрузила ученицам сейчас первые 3 урока и сделала предобучение, чтобы до старта им было не скучно ждать!

Кто еще не с нами? Заходите! Вас там ждут уроки!😍

ИДУ НА ЛУНАРИУМ (жми)

*напоминаю — обучение доступно в рассрочку/сплит/долями от 2000₽/мес Или рассрочка от меня @christinabelaya

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dealsolutions
@dealsolutions
87

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amazing_deal_offerss
@amazing_deal_offerss
63

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deals_loot
@deals_loot
7

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Dragtimes - сообщество петролхедов!
@dragtimes_ru
2K

Chrysler превратили в Mercedes

Американская компания Signature Autosports раздобыла Chrysler Crossfire и сделала вид, что это современная интерпретация легендарного Mercedes-Benz 300 SL Gullwing.

Создатели сразу подчёркивают, что не пытались построить точную копию. Это скорее современное прочтение классики. Поэтому вместо хромированного бампера здесь странноватый сплиттер, круглые светодиодные фары, крылья, будто позаимствованные у Shelby Cobra, а сзади — двойной выхлоп по центру и колёса Cosmis Racing, которые с оригинальным 300 SL сочетаются примерно так же, как кроссовки с фраком.

Впрочем, кое-что от Mercedes здесь действительно есть, и это не только эмблема на капоте. Chrysler Crossfire был ребёнком эпохи DaimlerChrysler. Почти 80% его компонентов позаимствованы у первого Mercedes-Benz SLK, включая платформу, двигатель и трансмиссию. То есть, Mercedes превратился в Chrysler, а теперь Chrysler снова пытаются превратить в Mercedes. Не запутайтесь.

Под капотом остался атмосферный 3,2-литровый V6 мощностью 215 л.с., работающий в паре с 5-ступенчатым автоматом и приводом на задние колёса. То есть динамика здесь примерно такая же, как у Crossfire двадцатилетней давности.

Зато цена отличается. За этот проект просят 299 950 долларов. То есть, это почти на 100 тысяч долларов дороже, чем новый Mercedes-AMG GT 63 S E Performance мощностью более 800 сил. И примерно в десять раз больше, чем стоил новый Crossfire в середине 2000-х.

Хотя, если задуматься, настоящий-то Mercedes 300 SL давно стоит миллионы долларов. Современный Mercedes его не выпускают. А если очень хочется Gullwing, то что такое несчастные 300 тысяч на мечту?!

#DT_Chrysler #DT_Mercedes

🚗 Dragtimes - канал | чат | донат

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unstoppable_announcements
@unstoppable_announcements
1K

COLDCARD POSTMORTEM : WHAT'S NEXT?

Everything you should know about the Coldcard hack in plain language, no technical rabbit holes.

WHAT HAPPENED

A bug Coldcard's wallet generation technique (mainly Mk3, 2021 onward) created wallets using "weak randomness".

As a result, something that is "impossible to guess" became "easy to guess". This led to ~500 wallets hacked in under half an hour.

The scary part that bug was there for years without anyone noticing it. Note that it's a third case over the ast couple of months.

Thorchain, Zcash and not COLDCARD... In all those cases the bug was there for years.

WHAT THIS MEANS FOR YOU

• Only a portion of @COLDCARDwallet devices are affected - but if you created your seed on a Coldcard, act as if yours is one of them.

• Important: importing your Coldcard-created seed into another wallet app does NOT help. The seed itself is weak. You need a NEW wallet created on a different device or app, then send/transfer the funds there.

• Other mainstream hardware wallets are NOT less safe because of this. This was one vendor's bug, not a flaw in hardware wallets as a concept. If you're searching for another hardware wallet we personally recommend @Trezor due to their long standing reputation in the industry.

HOW TO CHOOSE A WALLET (our take)

• Pick wallets built on documented, open standards. For hardware, Trezor is probably the best-equipped team in the industry. Ledger is big too, but has a history of privacy breaches.

• For software wallets, we (subjectively) recommend mobile wallets. Given the wallet is built per standards , modern mobile platforms offer the best out-of-the-box security. Combine that with basic security hygiene (regular OS updates, no porn browsing etc) you will get a fairly advanced level of security.

• Look for wallets with regular public audits. For instance, we pay for those ourselves - they're expensive but we believe they are needed to ensure capable external eyes are looking at your codebase.

• Look for endorsements from technical audiences. Back in the early days, some of the more through reviews we've been through were getting listed on resources like bitcoin dot org. Enormously grateful to the teama running those resources.

• if you have a large stash in self-custody then we recommend splitting that between 2-3 wallets/brands that meet standard criteria (see above). We personally, use @unstoppablebyhs for about 40% of our assets. despite that it's a product we build ourselves we also use @Trezor and @Ledger. There are other that we believe to be good mobile wallets out there. Do not keep all eggs in one basket is a good rule to follow in all aspects of life.

THE NEW REALITY

1) AI has made finding bugs dramatically easier - which is why we keep seeing flaws surface in code that sat in public view for years. Expect more of these, from everyone.

2) Open source projects are currently more exposed than closed source ones. You can't attack code that you don't see. So, AI scanning open source code puts a strain over a short term, but long term, open code that survives public scrutiny is the only thing that earns trust.

3) Finally, convincing people to self-custody just got harder. But pressure like this is what forges better security and better UX. Times like these set the new standards.

We just need to keep going!

Self custody is the only way to maintain freedom and independence long term.

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Склад Кешбэка | Промокоды & Скидки
@skladcashbacka
147

Кондиционер Сплит-система NEOLINE Airfresh NAM-09HN1_V2 комплект, площадь охлаждения/обогрева до 26 м², компрессор GMCC-TOSHIBA

Старая цена — 20,000₽ Новая цена — 12,000₽

Товар по ссылке

❗ Цена может отличаться в зависимости от аккаунт

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Краснодар, мкр. Молодёжный-Витамин
@molodezhnyi_vitamin
453

Сдается 1 ком. квартира на длительный срок по адресу: Душистая 65. В квартире есть вся необходимая техника: холодильник, стиральная машина, микроволновая печь, телевизор, сплитсистема. Разрешено проживание с животным. 20000₽+ком. услуги 89184638159 Владислав

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Промокоды ММ (Актуальные)
@mm_promokode
278

Кондиционер Сплит-система NEOLINE Airfresh NAM-09HN1_V2, компрессор GMCC-TOSHIBA, со скидкой на Яндекс Маркет ⭐️ 4.8 2462 отзыва - 7274 купили

🏷 Цена: 12 758 ₽ (с учётом карты Яндекс Пэй) ➡️https://market.yandex.ru/cc/AUGQoE?erid=5jtCeReNx12oajzg1LWq5ui

Реклама. ООО «Яндекс Маркет», ИНН 9704254424; erid: 5jtCeReNx12oajzg1LWq5ui

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Усть-Лабинск ИнфоГород
@infogorodul
287

"Хочу поднять вопрос о температуре на автовокзале.

Все лето там не работает сплит-система, хотя в том году все было хорошо. Наши пожилые люди с давлением и плохим самочувствием, которые приехали на приём к врачу, вынуждены часами сидеть и ждать своего автобуса в этой жаре."

От подписчика.

❓️ Кто был на автовокзале, неужели и правда, там не работают сплиты? 🤯

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А
Английский язык🇬🇧
@tg_engl1sh
156

Let’s talk about Marvel 🦸

Alex: I think Captain America: Civil War is the most emotional Marvel movie because it splits the Avengers into two sides.

Sam: I agree, but I still believe Tony Stark was right — he just wanted to protect the team from government control.

Alex: That’s true, but Steve Rogers couldn’t sign the Sokovia Accords because he trusted his own judgment more than any politician.

Sam: Anyway, my favorite phase is Phase Three because it includes Infinity War and Endgame, and the stakes felt so real.

Alex: Yeah, and the time travel concept in Endgame was confusing but also brilliant — it connected all the old movies perfectly.

Sam: Honestly, I just love how Marvel creates such a huge universe where even small characters get their own moments to shine.

Vocab emotional — эмоциональный split into two sides — разделить на две стороны government control — государственный контроль Sokovia Accords — Соковианские соглашения judgment — суждение stakes — ставки, риск time travel — путешествие во времени confusing — запутанный universe — вселенная shine — сиять, проявлять себя

tg_engl1sh🇬🇧

Ю
Юля помогает🔮Эзотерикам
@julee_pomogaet_ezo
361

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Д
Дайте два! | Скидки, дети и Москва
@kate_pro_dosug
142

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Д
ДИСКОНТ БЫТОВОЙ ТЕХНИКИ
@tehprofi
406

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У
Уралбиовет-Консалтинг
@vetwebinar
301

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