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Publicaciones del Canal
| 2 |  š ŠŠ°ŠŗŠ°Š½ŃŠøŃ: Middle ML Engineer
š¢ ŠŠ¾Š¼ŠæŠ°Š½ŠøŃ: ŠŠ¾Š¼ŠøŃŠµŃ Š ŠµŃŠæŃŠ±Š»ŠøŠŗŠø Š£Š·Š±ŠµŠŗŠøŃŃŠ°Š½ ŠæŠ¾ Š±ŠµŠ·Š¾ŠæŠ°ŃŠ½Š¾ŃŃŠø ŠæŠøŃŠµŠ²Š¾Š¹ ŠæŃŠ¾Š“ŃŠŗŃŠøŠø
ŠŃŠµŠ¼ Middle ML Engineer Š“Š»Ń ŃŠ°Š·ŃŠ°Š±Š¾ŃŠŗŠø Šø Š²Š½ŠµŠ“ŃŠµŠ½ŠøŃ AI/ML-ŃŠµŃŠµŠ½ŠøŠ¹ Š² ŃŃŠµŃŠµ Š±ŠµŠ·Š¾ŠæŠ°ŃŠ½Š¾ŃŃŠø ŠæŠøŃŠµŠ²Š¾Š¹ ŠæŃŠ¾Š“ŃŠŗŃŠøŠø ā Š¾Ń ŠæŠ¾Š“Š³Š¾ŃŠ¾Š²ŠŗŠø Š“Š°Š½Š½ŃŃ
Šø Š¾Š±ŃŃŠµŠ½ŠøŃ Š¼Š¾Š“ŠµŠ»ŠµŠ¹ Š“Š¾ Š·Š°ŠæŃŃŠŗŠ° ŃŠµŃŠµŠ½ŠøŠ¹ Š² production.
š ŠŠ¾ŠŗŠ°ŃŠøŃ: Š¢Š°ŃŠŗŠµŠ½Ń
š¢ Š¤Š¾ŃŠ¼Š°Ń: On-site
š ŠŠ°Š½ŃŃŠ¾ŃŃŃ: Full-time
š¼ Š£ŃŠ¾Š²ŠµŠ½Ń: Middle
š° ŠŠ°ŃŠæŠ»Š°ŃŠ°: ŠŗŠ¾Š½ŠŗŃŃŠµŠ½ŃŠ½Š°Ń, Š¾Š±ŃŃŠ¶Š“Š°ŠµŃŃŃ ŠæŠ¾ ŃŠµŠ·ŃŠ»ŃŃŠ°ŃŠ°Š¼ ŃŠ¾Š±ŠµŃŠµŠ“Š¾Š²Š°Š½ŠøŃ
Š§ŃŠ¾ ŠæŃŠµŠ“ŃŃŠ¾ŠøŃ Š“ŠµŠ»Š°ŃŃ:
ā¢ ŃŠ°Š·ŃŠ°Š±Š°ŃŃŠ²Š°ŃŃ Šø Š²Š½ŠµŠ“ŃŃŃŃ ŃŠµŃŠµŠ½ŠøŃ Š½Š° Š±Š°Š·Šµ Machine Learning / Deep Learning;
ā¢ ŃŠ°Š±Š¾ŃŠ°ŃŃ Ń NLP Šø Large Language Models;
ā¢ ŃŠ¾Š·Š“Š°Š²Š°ŃŃ ŃŠµŃŠµŠ½ŠøŃ Š“Š»Ń OCR Šø Document AI;
ā¢ ŃŠ°Š·ŃŠ°Š±Š°ŃŃŠ²Š°ŃŃ RAG-ŃŠøŃŃŠµŠ¼Ń, embeddings Šø semantic search;
ā¢ Š³Š¾ŃŠ¾Š²ŠøŃŃ Šø Š¾Š±ŃŠ°Š±Š°ŃŃŠ²Š°ŃŃ datasets Š“Š»Ń Š¾Š±ŃŃŠµŠ½ŠøŃ Š¼Š¾Š“ŠµŠ»ŠµŠ¹;
ā¢ Š·Š°Š½ŠøŠ¼Š°ŃŃŃŃ model training, fine-tuning Šø evaluation;
ā¢ Š²ŃŠ²Š¾Š“ŠøŃŃ ML-Š¼Š¾Š“ŠµŠ»Šø Š² production;
ā¢ ŃŠ°Š·ŃŠ°Š±Š°ŃŃŠ²Š°ŃŃ Šø ŠæŠ¾Š“Š“ŠµŃŠ¶ŠøŠ²Š°ŃŃ model serving;
ā¢ ŃŃŠ°ŃŃŠ²Š¾Š²Š°ŃŃ Š² ŠæŠ¾Š»Š½Š¾Š¼ Š¶ŠøŠ·Š½ŠµŠ½Š½Š¾Š¼ ŃŠøŠŗŠ»Šµ ML-ŠæŃŠ¾ŠµŠŗŃŠ¾Š².
Š§ŃŠ¾ Š¾Š¶ŠøŠ“Š°ŠµŠ¼:
ā¢ ŠæŃŠ°ŠŗŃŠøŃŠµŃŠŗŠøŠ¹ Š¾ŠæŃŃ ŃŠ°Š·ŃŠ°Š±Š¾ŃŠŗŠø ML/AI-ŃŠµŃŠµŠ½ŠøŠ¹;
ā¢ ŃŠ²ŠµŃŠµŠ½Š½Š¾Šµ ŠæŠ¾Š½ŠøŠ¼Š°Š½ŠøŠµ Machine Learning Šø Deep Learning;
ā¢ Š¾ŠæŃŃ ŃŠ°Š±Š¾ŃŃ Ń NLP / LLM;
ā¢ ŠæŠ¾Š½ŠøŠ¼Š°Š½ŠøŠµ RAG, embeddings Šø ŃŠ¾Š²ŃŠµŠ¼ŠµŠ½Š½ŃŃ
ŠæŠ¾Š“Ń
Š¾Š“Š¾Š² Šŗ ŠæŠ¾ŠøŃŠŗŃ;
ā¢ Š¾ŠæŃŃ ŠæŠ¾Š“Š³Š¾ŃŠ¾Š²ŠŗŠø Šø Š¾Š±ŃŠ°Š±Š¾ŃŠŗŠø datasets;
ā¢ ŠæŠ¾Š½ŠøŠ¼Š°Š½ŠøŠµ ŠæŃŠ¾ŃŠµŃŃŠ¾Š² Š¾Š±ŃŃŠµŠ½ŠøŃ, fine-tuning Šø Š¾ŃŠµŠ½ŠŗŠø ŠŗŠ°ŃŠµŃŃŠ²Š° Š¼Š¾Š“ŠµŠ»ŠµŠ¹;
ā¢ Š¾ŠæŃŃ ŠøŠ»Šø Ń
Š¾ŃŠ¾ŃŠµŠµ ŠæŠ¾Š½ŠøŠ¼Š°Š½ŠøŠµ deployment Šø production ML;
ā¢ ŃŠæŠ¾ŃŠ¾Š±Š½Š¾ŃŃŃ ŃŠ°Š¼Š¾ŃŃŠ¾ŃŃŠµŠ»ŃŠ½Š¾ Š²ŠµŃŃŠø ML-Š·Š°Š“Š°ŃŃ Š¾Ń ŠæŠ¾Š“Š³Š¾ŃŠ¾Š²ŠŗŠø Š“Š°Š½Š½ŃŃ
Š“Š¾ production.
ŠŃŠ½Š¾Š²Š½ŃŠµ Š½Š°ŠæŃŠ°Š²Š»ŠµŠ½ŠøŃ:
Machine Learning ā¢ Deep Learning ā¢ LLM ā¢ NLP ā¢ OCR ā¢ Document AI ā¢ RAG ā¢ Embeddings ā¢ Semantic Search ā¢ Fine-tuning ā¢ Model Evaluation ā¢ Production ML ā¢ Model Serving
Š£ŃŠ»Š¾Š²ŠøŃ:
ā¢ full-time ŃŠ°Š±Š¾ŃŠ°;
ā¢ ŃŠ°Š±Š¾ŃŠ° Š² Š¾ŃŠøŃŠµ;
ā¢ ŃŃŠ°ŃŃŠøŠµ Š² ŃŠµŠ°Š»ŃŠ½ŃŃ
Š³Š¾ŃŃŠ“Š°ŃŃŃŠ²ŠµŠ½Š½ŃŃ
AI/ML-ŠæŃŠ¾ŠµŠŗŃŠ°Ń
;
ā¢ Š²Š¾Š·Š¼Š¾Š¶Š½Š¾ŃŃŃ ŃŠ¾Š·Š“Š°Š²Š°ŃŃ ŃŠµŃŠµŠ½ŠøŃ Š“Š»Ń ŃŠøŃŃŠ¾Š²ŠøŠ·Š°ŃŠøŠø ŃŃŠµŃŃ Š±ŠµŠ·Š¾ŠæŠ°ŃŠ½Š¾ŃŃŠø ŠæŠøŃŠµŠ²Š¾Š¹ ŠæŃŠ¾Š“ŃŠŗŃŠøŠø;
ā¢ Š·Š°ŃŠ°Š±Š¾ŃŠ½Š°Ń ŠæŠ»Š°ŃŠ° Š¾Š±ŃŃŠ¶Š“Š°ŠµŃŃŃ ŠøŠ½Š“ŠøŠ²ŠøŠ“ŃŠ°Š»ŃŠ½Š¾ Š² Š·Š°Š²ŠøŃŠøŠ¼Š¾ŃŃŠø Š¾Ń Š¾ŠæŃŃŠ°.
š© Š ŠµŠ·ŃŠ¼Šµ: @davronbek_dev
š @uzpythonjobs | 199 |
| 3 | Savol:š”
Hozirda AI rivojlangan davrda algo uchun vaqt sarflash bu ortiqch ish emasmikin? Buning o'rniga system design chuquroq o'rganganish yaxshimikin?
Nima deb o'ylaysiz?
Algo Challenge: @algo_boost | 378 |
| 4 | 2^8 š
Claudeāga dam berishga arziguyilik bahona. Siz ham miyaga dam berib, bu videoni koārsangiz boāladi!
Hozirgi kundagi men uchun tinchlik bermaydigan mavzu haqida boālibdi)
Qaysi yoāl toāgāri? MAANG or StartUp ? (oylik yoki boylik) | 714 |
| 5 |  +1Ai bilan ko'p nazariy bilimlarni ko'chaytirish mumkin, lekin nazariy bilimlar o'zi yetarli emas, shunga qaramay yaqin kunlarda o'zim qiziqib yurgan mavzuklarni bir saytga jamladim (AI bilan albatta). Sizga ham foydali bo'lib qolishi mumkin balki. | 1 156 |
| 6 | Jamoamizga tajribali Middle ML Engineer qidiryapmiz.
Asosiy yoānalishlar:
* Machine Learning / Deep Learning
* LLM / NLP
* OCR va Document AI
* RAG / Embedding / Search
* Model training, fine-tuning va evaluation
* Production ML va model serving
Nomzoddan ML loyihalarni dataset tayyorlashdan boshlab productionāga chiqarishgacha boālgan jarayonni mustaqil olib bora olish tajribasi kutiladi.
š¢ Company: Oziq-ovqat xavfsizligi qo'mitasi
š¼ Full-time | On-site
š° Raqobatbardosh oylik, tajribaga qarab kelishiladi
š© Resume quyidagi kontaktlarga yuborishingiz mumkin:
@davronbek_dev | 1 482 |
| 7 |  Macāda terminali uchun kichik qoāllanma ai bilan tayorladik)
Ichida:
* Fish va Starship sozlash
* autosuggestion va iconālar
* foydali CLI toolālar
* Docker, API va network debugging
* monitoring va performance commandālari
Balki sizga ham foydasi tegib qolar!
š [Gist] | 943 |
| 8 |  Algoritmlarni osonroq va vizual tarzda oārganish uchun kichik saytcha
Bunda siz:
ā¢ Sorting va searching algoritmlarini qadam-baqadam kuzatishingiz
ā¢ Animatsiyalarni boshqarib, tajriba qilib koārishingiz
ā¢ Sodda tushuntirishlarni oāqishingiz
ā¢ Qisqa quizlar orqali bilimingizni sinashingiz mumkin
Koārib chiqingchi ;)
https://firdavsdev.github.io/algo-interactive-visualization | 1 639 |
| 9 |  +8š» ŠŃŠ¾Š“Š°ŠµŃŃŃ MacBook Pro 14ā (2021)
š Š„Š°ŃŠ°ŠŗŃŠµŃŠøŃŃŠøŠŗŠø:
ā¢ Apple M1 Pro
ā¢ 16 GB Unified Memory
ā¢ 512 GB SSD
ā¢ 14.2ā Liquid Retina XDR (3024Ć1964, 120 ŠŃ)
ā¢ Touch ID
š ŠŠ°ŃŠ°ŃŠµŃ:
ā¢ 418 ŃŠøŠŗŠ»Š¾Š²
ā¢ Š”Š¾ŃŃŠ¾ŃŠ½ŠøŠµ: ŠŠ±ŃŃŠ½ŃŠ¹
ā¢ ŠŠ°ŠŗŃŠøŠ¼Š°Š»ŃŠ½Š°Ń ŠµŠ¼ŠŗŠ¾ŃŃŃ: 90%
š¦ ŠŠ¾Š¼ŠæŠ»ŠµŠŗŃŠ°ŃŠøŃ:
ā
ŠŃŠøŠ³ŠøŠ½Š°Š»ŃŠ½Š°Ń ŠŗŠ¾ŃŠ¾Š±ŠŗŠ°
ā
ŠŃŠøŠ³ŠøŠ½Š°Š»ŃŠ½ŃŠ¹ Š·Š°ŃŃŠ“Š½ŃŠ¹ Š°Š“Š°ŠæŃŠµŃ Šø ŠŗŠ°Š±ŠµŠ»Ń
ā
ŠŠ¾ŠŗŃŠ¼ŠµŠ½ŃŃ
ā
iCloud Š¾ŃŠ²ŃŠ·Š°Š½, Š³Š¾ŃŠ¾Š² Šŗ Š½Š¾Š²Š¾Š¼Ń Š²Š»Š°Š“ŠµŠ»ŃŃŃ
š Š”Š¾ŃŃŠ¾ŃŠ½ŠøŠµ:
ā¢ ŠŠ¾Š»Š½Š¾ŃŃŃŃ ŠøŃŠæŃŠ°Š²ŠµŠ½, ŃŠ°Š±Š¾ŃŠ°ŠµŃ Š±ŠµŠ· ŠŗŠ°ŠŗŠøŃ
-Š»ŠøŠ±Š¾ ŠæŃŠ¾Š±Š»ŠµŠ¼.
ā¢ ŠŃŃŃ Š½ŠµŠ±Š¾Š»ŃŃŠøŠµ ŠŗŠ¾ŃŠ¼ŠµŃŠøŃŠµŃŠŗŠøŠµ ŃŠ°ŃŠ°ŠæŠøŠ½Ń Š½Š° ŠŗŃŃŃŠŗŠµ (Š²ŠøŠ“Š½Š¾ Š½Š° ŃŠ¾ŃŠ¾), Š½Š° ŃŠ°Š±Š¾ŃŃ Š½Šµ Š²Š»ŠøŃŃŃ.
š° Š¦ŠµŠ½Š°: 600 $
š¤ Š¢Š¾ŃŠ³ ŃŠ¼ŠµŃŃŠµŠ½
šŠŠ¾ŃŠ¾Š“: Š¢Š°ŃŠŗŠµŠ½Ń
š Š¢ŠµŠ»ŠµŃŠ¾Š½: +998 94 670-73-07
š¬ Telegram: @ulugbek_axtamov | 293 |
| 10 |  +1š„ Sotiladi: Kuchli Gaming / Workstation Kompyuteri š„
Deyarli ishlatilmagan, ideal holatda. Barcha komplektatsiyasi va original qutilari (karobkalari) mavjud. Kompyuter atigi 5 oy oldin yigāilgan.
š Texnik xususiyatlari:
ā¢ Motherboard: ASUS Z790 DF WiFi
ā¢ Protsessor: Intel Core i9-14900KF
ā¢ Sovutish tizimi: 360 Pro Liquid Cooler
ā¢ Operativ xotira: 64 GB DDR5 (32 GB Ć 2, 6000 MHz)
ā¢ Videokarta: NVIDIA GeForce RTX 5070 Ti 16 GB
ā¢ SSD: Kingston 1 TB
ā¢ Korpus: Thermaltake Aqua
ā¢ Quvvat bloki: DeepCool 1000W
ā¢ Sichqoncha: VT9 Pro
ā
Oāyinlar, sunāiy intellekt, videomontaj, dasturlash va boshqa yuqori yuklama talab qiladigan ishlar uchun aālo darajadagi konfiguratsiya.
š° Narxi: 2 500 AQSh dollari (kelishiladi).
š© Xarid qilish istagida boālganlar Telegram orqali bogālanishlari mumkin:
@data_professor | 384 |
| 11 |  So'nggi paytlarda AI va AI agentlar rivojini kuzatib bitta narsani aniqroq tushunyapman:
Bu skill'lar AI davrida ham o'lmaydi.
ā¢ Distributed Systems
ā¢ Latency, timeout, retry, backoff
ā¢ Idempotency
ā¢ CAP theorem
ā¢ Consistency models
ā¢ Database internals
ā¢ Postgres internals
ā¢ Caching strategy
ā¢ Queue/event-driven architecture
ā¢ Kafka internals
ā¢ API Gateway
ā¢ Rate limiting
ā¢ Circuit breaker
ā¢ Observability
ā¢ Scalability patterns
ā¢ Multi-tenant architecture
ā¢ System design interview practice
Oddiy code yozish tobora arzonlashyapti.
Lekin productionāda ishlaydigan buzilganda tiklanadigan scale boāladigan system qurish hali ham qimmat skill.
Shuning uchun menimcha kelajakda kuchli developer bulish uchun faqat framework bilish yetmaydi:
Framework o'zgaradi.
AI tool o'zgaradi.
Library o'zgaradi.
Lekin system thinking qoladi.
p.s) Algorithm sizni kuchli senior qilmaydi. U faqat eshikdan (interview) kirishda filter. Real ishda sizni system design, architecture, debugging, ownership kutaradi.
ā¢ Arrays / HashMap
ā¢ Two pointers
ā¢ Sliding window
ā¢ Stack / Queue
ā¢ Binary search
ā¢ Linked list
ā¢ Trees
ā¢ Heap / Priority Queue
ā¢ Graph BFS/DFS
ā¢ Dynamic Programming basic
ā¢ Intervals
ā¢ Backtracking basic
ā¢ Top K patterns
Links:
ā¢ Grokking System Design
ā¢ System Design Cheatsheet
ā¢ Python Design Patterns #1
ā¢ Python Design Patterns #2
ā¢ System Design Primer
ā¢ System Design Academy
ā¢ Best system Design Resources
ā¢ https://t.me/links_for_mine_prep/184
ā¢ https://t.me/links_for_mine_prep/210
Sharing is caringš¤
Ā» @davron_coder | 630 |
| 12 | Qurbon hayiti muborak boālsin hamkasblar! š | 713 |
| 13 |  +1Yangi dokumentatsiyasi mavjud bo'lmagan loyihaga qo'shilganizda ast qotishi mumkin bo'lgan pluggin ekan.
Codebase tahlil qilib sizga archecture chizib animatsiyon holatga ko'rsatib bera olar ekan
[more] | 751 |
| 14 |  Zamon bilan xam nafas bo'lib yashash kerak, lekin bu ai agent erasi hech tuxtagisi kelmaydi, bugun chiqan future change'lar kechagi change'ga to'g'ri kelmay qolmoqda. MD fayl'larni mukammal yozish haqida youtube'da kurilmagan video darsliklar qolmadi ... šæ
Yana qaysilari qolib ketdi?
ā¢ Claude
ā¢ Codex
ā¢ Gemini (antigravity.google)
ā¢ OpenCode
ā¢ GitHub Copilot
ā¢ Cursor
ā¢ Windsurf
ā¢ etc | 872 |
| 15 |  +2Kechagi post izohlarida tokenlarni tejash bo'yicha ajoyib takliflar bo'ldi. Ular bo'yicha alohida post qilaman. Hozir esa o'zimning yechimimni aytaman. Bu agentlar.
Yechimga kelishdan avval men Claude codedan mening foydalanish uslubimni to'liq tahlil qilib chiqishni so'radim. Sababi, dasturlash faqat kod yozishdan iborat emas, rejalash, maslahatlashish, dokumentasiya va hokazo mingta mayda ishlar ham bor. Men esa (ko'pchilik kabi) hammasi uchun standart opusdan foydalanar edim. Tahlil esa faqatgina 1% vazifalar opusga qolgan 99% ni esa bemalol arzonroq sonnet va suv-tekin haiku modellariga topshirish mumkinligini ko'rsatdi (1-rasm).
Masalan, haiku opusga nisbatan 15 barobar kamroq token yeyishini men shu tahlildan keyin bildim (Claude o'zi aytdi š
). Va umuman olganda agar boshidan har bir turdagi vazifalar uchun alohida agent ishlatganimda qancha token tejashim mumkinligini ham solishtirib berdi - 85% (2-rasm).
Keyin esa claude'ning o'zidan mening loyihalarim va foydalanish uslubimdan kelib chiqqan holda agentlar yozib berishni so'radim va u menga 3-rasmda ko'rsatilgan agentlarni tavsiya qildi.
Va bularni yaratish uchun ham tayyor prompt yozib berdi. Endi har gal kod yozganimda asosiy agent unga qoy'ilgan vazifadan kelib chiqqan holda boshqa agentlarni ishga tushiradi va ular o'zi biriktirlgan model asosida ishlaydi. Bunda asosiy hal qilvuchi agent sonnet asosida ishlaydi.
Xullas agar sizga ham multi-agent claude code muhiti qiziq bo'lsa sizning ish uslubingizni tahlil qilib, sizga mos agentlar yaratib beradigan promptni 1-izohda qoldiraman. š
P.s. Natijalar bilan izohda boŹ»lishamiz, siz qanday foydalanar ekansiz va sizga qanday agentlar tavsiya qilindi. | 931 |
| 16 | Iphone ishlatadiganla sizlarga ham notifications kelmayaptimi telegramdan, locked paytlari? ( | 343 |
| 17 |  +2š Yangi kitob ustida ishlayapman: "AsyncIO: Nega ishlamayapti?"
Ochiq feedback bering:
1ļøā£ Tema qiziqmi? Bu kitob sizga kerakmi?
2ļøā£ Qaysi bobni eng oldin ko'rishni xohlardingiz?
3ļøā£ O'zingiz async bilan duch kelgan, lekin internet'da yechimi yo'q muammo bormi? Aytib bering - kitobga qo'shaman, sizning ismingiz bilan.
4ļøā£ 1-bob namunasini kim ko'rmoqchi - DM yozing, jo'nataman)) | 927 |
| 18 |  Breached š„ | 176 |
| 19 |  Mensaje de video | 1 |
| 20 | Junior, Juniors + uchun ajoyib imkoniyat boālishi mumkin. š
Oāz bilimlarizni real loyihalarda sinab yanada mustahkamlab olish imkoniyati, manimcha hozirgi ai agentlar davrida junior stajrovka(amaliyot) qilib olishlari uchun zoār imkoniyat!
https://t.me/coderwayuz/880 | 1 224 |
