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DataSpoof

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Learn Data Science https://dataspoof4081.graphy.com/membership Artificial Intelligence Machine Learning Data Science Deep learning Computer vision NLP Big data

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📈 Telegram kanali DataSpoof analitikasi

DataSpoof (@dataspoof) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 16 138 obunachidan iborat bo'lib, Taʼlim toifasida 12 559-o'rinni va Hindiston mintaqasida 26 707-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 16 138 obunachiga ega bo‘ldi.

20 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -151 ga, so‘nggi 24 soatda esa 0 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 7.89% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 0 marta ko‘riladi; birinchi sutkada odatda 0 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 0 ta reaksiya keladi.
  • Tematik yo‘nalishlar: Kontent api, llm, pipeline, +9183182, engineer kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
Learn Data Science https://dataspoof4081.graphy.com/membership Artificial Intelligence Machine Learning Data Science Deep learning Computer vision NLP Big data

Yuqori yangilanish chastotasi (oxirgi ma’lumot 21 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

16 138
Obunachilar
Ma'lumot yo'q24 soatlar
-397 kunlar
-15130 kunlar
Postlar arxiv
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Andrew karpathy launched its llm course https://github.com/karpathy/LLM101n

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Complete Data Science end to end training Duration- 8 months For curriculum and fees structure https://www.dataspoof.info/training/

DataSpoof
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Generative AI in Search and Recommendations.pdf2.06 MB

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Introduction_to_apache_kafka.pdf10.15 KB

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Gpt4o

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Education is shifting. Teachers beware. Kids are going to get great tutoring going forward. The future is so, so bright. #OpenAI #gpt4o #ai #gpt #llms

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Large Language Models _ _ CHEAT SHEET.pdf1.31 MB

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Git for Quants.pdf0.90 KB

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Cicd notes

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CICD for Freshers_Experienced .pdf4.16 MB

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The basics of reinforcement learning in simple words https://www.dataspoof.info/post/basics-of-reinforcement-learning/

DataSpoof
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Reflecting on a memorable interview experience with Kotak Mahindra Bank for the SDE-2 (Data Engineering) role! 🌟 It comprised four stimulating rounds, featuring two bar raiser and two internal rounds. Round 1: Delved deep into DS & Algo, SQL data modeling, and Data Warehousing, setting the stage for a robust discussion. Round 2: Focused on Pipeline designing and Spark, challenging me to showcase my skills in designing efficient data pipelines. Round 3: Dived into SQL and Spark optimization, where I had the opportunity to demonstrate my expertise in enhancing performance. Round 4: A dynamic mix of everything, including streaming and writing ETL for various scenarios, truly putting my skills to the test.

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𝗣𝗪𝗖 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 (𝗗𝗮𝘁𝗮 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫) ⭐→ The whole interview process had 3 rounds of 1 hour each. 🔸 The first round was an extensive discussion about the projects I was handling and a few coding questions on SQL & Python. There were questions like the following: → Optimisation techniques used in projects; Issues faced in the project; Hadoop questions. 🔸 After clearing this round, I moved on to the next round, which was a Case-Study based round. I was asked scenario-based questions & the interviewer asked multiple questions on Spark, like: → Spark job process; Optimizations of spark; Sqoop interview questions. After this, I was asked a few Coding questions & SQL coding questions, which I successfully answered. 🔸 Lastly, there was a Managerial Round where I was asked a lot of technical and advanced questions like: → Architecture of spark, hive, Hadoop; Overview of MapReduce job process; Joins to use in spark; Broadcast join & lastly Different joins available.

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Jenkins Basics for freshers_experienced.pdf4.77 MB

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photo content