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Excited to share that I successfully passed the Mobile Application Developer AI Interview and earned certification from Micro1. This assessment evaluated technical knowledge, problem-solving abilities, and communication skills across mobile application development concepts. I'm grateful for this achievement and look forward to exploring opportunities in Android, iOS, Flutter, Kotlin, Java, and cross-platform mobile development. #Micro1 #MobileDeveloper #AndroidDeveloper #iOSDeveloper #FlutterDeveloper #ReactNative #Kotlin #Java #Swift #MobileAppDevelopment #SoftwareEngineer #SoftwareDevelopment #TechCareers #AIInterview #FullStackDeveloper #CloudComputing #CareerGrowth

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तेजी से बदल रहा ट्रेंड, आप भी हो जाइए तैयार... AI बॉट के साथ हो सकता है आपका अगला जॉब इंटरव्यू; ऐसे करें तैयारी . . . #Informationtechnology #Artificialintelligence #techtip #Technology #AI #job #interview #AIinterview republicbharat.com/india/edu…

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🧠 ML Interview Question by AIML.com: 𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐒𝐞𝐪𝐮𝐞𝐧𝐜𝐞 𝐌𝐨𝐝𝐞𝐥𝐬? 𝐊𝐞𝐲 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐚𝐧𝐝 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 📖 Article Link: aiml.com/what-are-sequence-m… 𝘸𝘩𝘦𝘯 𝘺𝘰𝘶 𝘢𝘴𝘬 𝘚𝘪𝘳𝘪 𝘵𝘰 𝘴𝘦𝘵 𝘢𝘯 𝘢𝘭𝘢𝘳𝘮, 𝘸𝘩𝘦𝘯 𝘎𝘰𝘰𝘨𝘭𝘦 𝘛𝘳𝘢𝘯𝘴𝘭𝘢𝘵𝘦 𝘧𝘭𝘪𝘱𝘴 𝘺𝘰𝘶𝘳 𝘌𝘯𝘨𝘭𝘪𝘴𝘩 𝘮𝘦𝘴𝘴𝘢𝘨𝘦 𝘪𝘯𝘵𝘰 𝘑𝘢𝘱𝘢𝘯𝘦𝘴𝘦, 𝘸𝘩𝘦𝘯 𝘛𝘦𝘴𝘭𝘢'𝘴 𝘢𝘶𝘵𝘰𝘱𝘪𝘭𝘰𝘵 𝘱𝘳𝘦𝘥𝘪𝘤𝘵𝘴 𝘢 𝘱𝘦𝘥𝘦𝘴𝘵𝘳𝘪𝘢𝘯'𝘴 𝘯𝘦𝘹𝘵 𝘮𝘰𝘷𝘦, 𝘰𝘳 𝘸𝘩𝘦𝘯 𝘈𝘮𝘦𝘳𝘪𝘤𝘢𝘯 𝘌𝘹𝘱𝘳𝘦𝘴𝘴 𝘧𝘭𝘢𝘨𝘴 𝘢 𝘴𝘶𝘴𝘱𝘪𝘤𝘪𝘰𝘶𝘴 𝘵𝘳𝘢𝘯𝘴𝘢𝘤𝘵𝘪𝘰𝘯, - they all rely on ONE family of models Sequence Models. The reason they matter is simple: most real-world data isn't independent. Words depend on the words before them. Stock prices depend on yesterday. A pedestrian's next step depends on their last three. Traditional ML assumes i.i.d. data, and that assumption breaks the moment order matters. 📖 In this article, AIML.com breaks down everything you need to know: 🔹 What sequence models are & why order in data matters 🔹 Why traditional ML fails on sequential, non-i.i.d. data 🔹 RNNs: the foundation, and their vanishing gradient flaw 🔹 LSTMs: how memory cells solve long-range dependencies 🔹 GRUs: a leaner, faster cousin of LSTMs 🔹 Transformers: self-attention powering BERT, GPT & more 🔹 9 real-world applications across industries 💬 Interview tip: This question is a staple in NLP, Deep Learning, and Generative AI interviews. Interviewers use it because it tests three things in one shot: your grasp of the RNN → LSTM → GRU → Transformer evolution, the 𝘸𝘩𝘺 behind each leap, and your ability to map theory to real products. 🔔 Follow @OfficialAIML on X for more interview prep resources ❤️ Like and Share the knowledge for wider reach - this is a free resource which can empower millions! 🚀 Preparing for ML / LLM interviews? Join AIML.com, the world's largest repository of ML interview questions and quizzes - Built by learners, for learners #AIMLCom #AIInterview #AIJobs #MLJobs #MLCareers #MachineLearning #DeepLearning #MLInterview #NLP #SequenceModels #RNN #LSTM #Transformers #AICareers

AI System design round at Amazon for L5/L6 AI Engineer ($400K TC): Color preference prediction system for sponsored product recommendations. Interviewer: "You’re showing color variants in Sponsored Products ads (e.g. red hoodie vs black hoodie). How do you build a real-time ML system that predicts which exact color a user is most likely to click/buy?" #Amazon #SystemDesign #MLEngineering #AIInterview

Interviewer has no idea Link in bio #aiinterview #job #interview #jobhunt #lockedinai

🧠 ML Interview Question by AIML.com: 𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐑𝐞𝐬𝐍𝐞𝐭 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 📖 Article Link: aiml.com/explain-resnet-arch… A favorite at FAANG ML interviews, and for good reason. ResNet didn't just win ImageNet 2015. It unlocked the era of truly deep networks. The numbers still impress: ✅ 3.57% top-5 error on ImageNet ✅ 152 layers: 8x deeper than VGG ✅ Lower computational complexity than VGG-19 The breakthrough wasn't more layers. It was a reframing: instead of learning a direct mapping H(x), learn the residual F(x) = H(x) − x. Skip connections did the rest, and that same idea now lives inside nearly every Transformer and LLM you've used this week. What's inside the article: 👉 The "degradation problem": why deeper networks got worse, not better 👉 How residual learning fixes it 👉 BasicBlock vs. Bottleneck Block 👉 Side-by-side comparison: VGG-19, ResNet-18/34/50/152 👉 Stage-by-stage walkthrough of ResNet-18 👉 Video explanations included 💬 Interview tip: Bonus points if you connect ResNet to today's models. Look at the pattern side by side: 𝐑𝐞𝐬𝐧𝐞𝐭 𝐁𝐥𝐨𝐜𝐤: 𝘹 𝘍(𝘹), where 𝘍 is a small stack of convolutions 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐛𝐥𝐨𝐜𝐤: 𝘹 𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯(𝘹), 𝘵𝘩𝘦𝘯 𝘹 𝘍𝘍𝘕(𝘹) Same residual skeleton - just swap convolutions for attention. ❤️ Interviewers love candidates who see that the 2015 paper is still running inside GPT-5 🚀 Preparing for ML / LLM interviews? Join AIML.com, the world's largest repository of ML interview questions - Built by learners, for learners. ➡️ 400 most-asked ML interview questions ➡️ 600 quiz questions across AI/ML topics #AIMLCom #AIInterview #AIJobs #MLJobs #MLCareers #MLAlgorithm #MachineLearning #DeepLearning #MLInterview #ComputerVision #ResNet #AICareers

Just implemented real-time AI note generation according to the interviewer's question and the AI response. #SaaS #AI #buildinpublic #AIInterview

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Befor the interview , I feel so exaust but this was my first interview on intersala , now I feel lutere 🫠🫠🫠🫠 #firstinterview #intersala #web #dev #aiinterview

Train like it’s the real interview. See what HR sees, get professional AI feedback on your answers and delivery, and improve before it actually counts. Your next opportunity deserves preparation that’s smart and realistic. #PrepoAI #InterviewPrep #AIInterview

🤖✨ We are starting a new dialogue. Our first interview conducted with artificial intelligence — ChatGPT — is now live. 🎨💡 At the intersection of design, creativity, and technology, we follow the traces of questions, intuition, and the future. #AIInterview #ChatGPT