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Artificial Intelligence && Deep Learning

Artificial Intelligence && Deep Learning

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Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:

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๐Ÿ“ˆ Telegram kanali Artificial Intelligence && Deep Learning analitikasi

Artificial Intelligence && Deep Learning (@deeplearning_ai) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 58 019 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 2 290-o'rinni va Hindiston mintaqasida 5 977-o'rinni egallagan.

๐Ÿ“Š Auditoriya koโ€˜rsatkichlari va dinamika

ะฝะตะฒั–ะดะพะผะพ sanasidan buyon loyiha tez oโ€˜sib, 58 019 obunachiga ega boโ€˜ldi.

25 Iyun, 2026 dagi oxirgi maโ€™lumotlarga koโ€˜ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -204 ga, soโ€˜nggi 24 soatda esa -8 ga oโ€˜zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya oโ€˜rtacha 9.58% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni toโ€˜playdi.
  • Post qamrovi: Har bir post oโ€˜rtacha 5 556 marta koโ€˜riladi; birinchi sutkada odatda 0 ta koโ€˜rish yigโ€˜iladi.
  • Reaksiyalar va oโ€˜zaro taโ€™sir: Auditoriya faol: har bir postga oโ€˜rtacha 16 ta reaksiya keladi.
  • Tematik yoโ€˜nalishlar: Kontent github, learning, estimation, dataset, engineer kabi asosiy mavzularga jamlangan.

๐Ÿ“ Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida taโ€™riflaydi:
โ€œChannel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:โ€

Yuqori yangilanish chastotasi (oxirgi maโ€™lumot 26 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli boโ€˜lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim taโ€™sir nuqtasiga aylantirishini koโ€˜rsatadi.

58 019
Obunachilar
-824 soatlar
-287 kunlar
-20430 kunlar
Postlar arxiv
650 Free Online Programming & Computer Science Courses You Can Start This July join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://www.freecodecamp.org/news/650-free-online-programming-computer-science-courses-you-can-start-this-summer/

Best Training & Certification Courses for Professionals | Edureka * PGP in AI & Machine Learning * Data Scientist Master Program * Cloud Architect Masters Program * ..... join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://www.edureka.co/all-courses

Best Training & Certification Courses for Professionals | Edureka * PGP in AI & Machine Learning * Data Scientist Master Prog
Best Training & Certification Courses for Professionals | Edureka * PGP in AI & Machine Learning * Data Scientist Master Program * Cloud Architect Masters Program * ..... join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI

Review: FCN โ€” Fully Convolutional Network (Semantic Segmentation) Covered: * From Image Classification to Semantic Segmentation * Upsampling Via Deconvolution * Fusing the Output * Results join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://towardsdatascience.com/review-fcn-semantic-segmentation-eb8c9b50d2d1

Implement Back Propagation in Neural Networks join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://medium.com/coinmonks/implement-back-propagation-in-neural-networks-ed09897593e7

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Free 6-Hour Data Science Course for Beginners This course covers: * foundations of data science * data sourcing * coding for data scientists * mathematics for data scientists * statistics join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://www.freecodecamp.org/news/data-science-course-for-beginners/

1. 10 New Things I Learnt from fast.ai v3 2. 2019 deep learning course Practical Deep Learning for Coders, v3. 10 learning points as such: 1. The Universal Approximation Theorem 2. Neural Networks: Design & Architecture 3. Understanding the Loss Landscape 4. Gradient Descent Optimisers 5. Loss Functions 6. Training 7. Regularisation 8. Tasks 9. Model Interpretability 10. Appendix: Jeremy Howard on Model Complexity & Regularisation join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI https://towardsdatascience.com/10-new-things-i-learnt-from-fast-ai-v3-4d79c1f07e33

SEVEN NEW COURSES that cover Python, R, and SQL. First up is Analyzing Business Data in SQL, where youโ€™ll learn how to write SQL queries to calculate key business metrics and produce report-ready results. Plus our Introduction to Text Analysis in R course, where youโ€™ll learn how to wrangle and visualize text, perform sentiment analysis, and run and interpret topic models. Courses : 1. Writing Functions and Stored Procedures in SQL Server 2. Analyzing Business Data in SQL 3. Feature Engineering for Machine Learning in Python 4. Introduction to Seaborn (in Python) 5. Advanced Dimensionality Reduction in R 6. Introduction to Text Analysis in R 7. Intermediate Interactive Data Visualization with plotly in R 1. https://www.datacamp.com/courses/writing-functions-and-stored-procedures-in-sql-server?utm_medium=email&utm_source=customerio&utm_campaign=course_7996 2. https://www.datacamp.com/courses/analyzing-business-data-in-sql?utm_medium=email&utm_source=customerio&utm_campaign=course_15268 3. https://www.datacamp.com/courses/feature-engineering-for-machine-learning-in-python?utm_medium=email&utm_source=customerio&utm_campaign=course_14336 4. https://www.datacamp.com/courses/introduction-to-seaborn?utm_medium=email&utm_source=customerio&utm_campaign=course_15192 5. https://www.datacamp.com/courses/advanced-dimensionality-reduction-in-r?utm_medium=email&utm_source=customerio&utm_campaign=course_10590 6. https://www.datacamp.com/courses/introduction-to-text-analysis-in-r?utm_medium=email&utm_source=customerio&utm_campaign=course_14290 7. https://www.datacamp.com/courses/intermediate-interactive-data-visualization-with-plotly-in-r?utm_medium=email&utm_source=customerio&utm_campaign=course_7193 join channel ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI .

Decoding the Best Papers from ICLR 2019 โ€“ Neural Networks are Here to Rule ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://www.analyticsvidhya.com/blog/2019/05/best-papers-iclr-2019/

Diving deeper into Reinforcement Learning with Q-Learning Join๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://medium.com/free-code-camp/diving-deeper-into-reinforcement-learning-with-q-learning-c18d0db58efe

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models paper โ€” arxiv๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ https://arxiv.org/pdf/1905.08233.pdf video โ€” youtube๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ https://www.youtube.com/watch?v=p1b5aiTrGzY join channel ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI .

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI

Few-Shot Adversarial Learning of Realistic Neural Talking Head Models ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI

Stanford Machine Learning Content 01 and 02: Introduction, Regression Analysis and Gradient Descent 03: Linear Algebra - review 04: Linear Regression with Multiple Variables 05: Octave[incomplete] 06: Logistic Regression 07: Regularization 08: Neural Networks - Representation 09: Neural Networks - Learning 10: Advice for applying machine learning techniques 11: Machine Learning System Design 12: Support Vector Machines 13: Clustering 14: Dimensionality Reduction 15: Anomaly Detection 16: Recommender Systems 17: Large Scale Machine Learning 18: Application Example - Photo OCR 19: Course Summary http://www.holehouse.org/mlclass/ ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI

Deep Learning lecture The full deck of (600+) slides, by Gilles Louppe: ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://glouppe.github.
Deep Learning lecture The full deck of (600+) slides, by Gilles Louppe: ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://glouppe.github.io/info8010-deep-learning/pdf/lec-all.pdf

Deep learning lecture
Deep learning lecture

Not just another GAN paper โ€” SAGAN โ€“ Towards Data Science ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://towardsdatascience.com/not-just-another-gan-paper-sagan-96e649f01a6b

Diving into Deep Convolutional Semantic Segmentation Networks and Deeplab_V3 ๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡๐Ÿ‘‡ @DeepLearning_AI . https://sthalles.github.io/deep_segmentation_network/