Computer Vision (Mohirdev)

Dasturlash bo‘yicha 15 yillik tajribaga ega va o‘qitish bo‘yicha 8 yillik tajribaga ega mutaxassisdan Computer Vision sohasini o'rganing
 

Kurs tarkibi

1 Computer Vision uchun Matplotlib

02.01. 1.1. Ma'lumotlarni vizuallashtirishga kirish (Introduction to data visualization)
02.02. 1.2. Matplotlib kutubxonasiga kirish (Introduction to Matplotlib library)
02.03. 1.3. Colab Dasturlash muhiti (Colab development environment)
02.04. 1.4 Nuqtalar orqali ma'lumotlarni tasvirlash (Scatter plots)
02.05. 1.5 Matplotlib figure bilan ishlash (Matplotlib figure)
02.06. 1.6 Matnlar bilan ishlash (Matplotlib text)
02.07. 1.7 Matplotlib plot
02.08. 1.8 Amaliyot. Parabolaning grafigini chizing (practice parabola)
02.09. 1.9 Bar chart
02.10. 1.10 Pie chart
02.11. 1.11 Ikki o‘lchamli array(massiv) bilan ishlash (2d array,nested list)
02.12. 1.12 Bir nechta grafiklar bilan ishlash (Subplots)
02.13. 1.13 matplotlib rasmlarni tasvirlash (imshow)
02.14. Bo'lim bo'yicha test

2 Computer Vision uchun matematika

03.01. 2.1. NumPy kutubxonasiga kirish (Intro to NumPy)
03.02. 2.2 NumPy array yaratish va uning xossalarini o‘rganish (Creating a NumPy array and its properties)
03.03. 2.3. NumPy arrayning asosiy arifmetik amallari (Basic NumPy Operations)
03.04. 2.4 NumPy arrayning elementlariga murojaat qilish (NumPy array indexing)
03.05. 2.5 NumPy arrayning elementlarini ajratib olish (NumPy array slicing)
03.06. 2.6 NumPy arrayning funksiyalari (Aggregation functions)
03.07. 2.7 Fayldan ma'lumotlarni yuklab olish (Importing data in NumPy)
03.08. 2.8 NumPy array shaklini o'zgartirish(Reshaping in NumPy)
03.09. 2.9 MNIST DATASET
03.10. Bo'lim bo'yicha yakuniy test

3 Tasvirga ishlov berish va Pillow kutubxonasiga kirish

04.01. 1. Pillow kutubxonasiga kirish (Introduction to Pillow)
04.02. 2. Pillow kutubxonasi orqali tasvirlarni yuklash va tasvirlarning xususiyatlari bilan ishlash (Opening and displaying images using Pillow)
04.03. 3. Tasvir ustida boshlang‘ich amallar (Basic image operations)
04.04. Bo'lim bo'yicha yakuniy test

4 Computer Vision with OpenCV

05.01. 1. Kompyuter ko'rishga kirish (Introduction to Computer Vision)
05.02. 2. OpenCV kutubxonasiga kirish (Introduction to OpenCV)
05.03. 3. Pixel nima? (Introduction to Pixel)
05.04. 4. Tasvirni yuklash, tasvirlash va saqlash (Load, Show, and Save)
05.05. 5. Tasvirni o'lchamini o'zgartirish (Resize image)
05.06. 6. Chiziq chizish (Drawing Basic Shapes Line)
05.07. 7. Aylana chizish (Drawing Basic Shapes Circle)
05.08. 8. To'rtburchak chizish (Drawing Basic Shapes rectangle)
05.09. 9. Matn chizish (Drawing Basic Shapes text)
05.10. 10. Ko'pburchak chizish (Drawing polygon)
05.11. 11. Tasvir ustida arifmetik amallar bajarish (Image Arithmetic)
05.12. 12. Image Blending
05.13. 13. Image Blending Assignment
05.14. 14. Tasvir ustida Mantiqiy amallar (Logical operations)
05.15. 15. Konvolyutsiya operatsiyasi (convolution operation)
05.16. 16. Chegaralar ( Borders)
05.17. 17. 2D filtri (filter2D)
05.18. 18. Tasvirga ishlov berish (xiralashtirish) ( Image Processing (Blur))
05.19. 19. Image Processing (Blur) Assignment
05.20. 20. Tasvirni konvertatsiya qilish (chegara) (Image Conversion (threshold))
05.21. 21. Range
05.22. 22. RANG NAZARIYASI (COLOR THEORY (Range))
05.23. 23. Svetoforni segmentatsiyalash (LOYIHA) (Traffic light segmentation (PROJECT))
05.24. 24. Svetoforni segmentatsiyalash (LOYIHA) (Svetoforni segmentatsiyalash (LOYIHA) (Traffic light segmentation (PROJECT)))
05.25. 25. MORFOLOGIYA amallari (MORPHOLOGY OPERATIONS)
05.26. 26. Konturlar (Contours)
05.27. 27. Kontur iyerarxiyasi(contours hierarchy)
05.28. 28. Konturlarni chizish (boundingRect) (draw contours (boundingRect))
05.29. 29. Konturlarni chizish (boundingRect) (draw contours (boundingRect))
05.30. 30. Kontur xususiyatlari yuzasi (Contour Features area)
05.31. 31 Kontur xususiyatlari uzunligi (Contour Features length)
05.32. 32. Konturning taxminiyligi (Contour Approximation)
05.33. 33. Chegarani aniqlash (edge detection)
05.34. 34 Aylanani aniqlash ( blob detection)
05.35. Bo'lim bo'yicha yakuniy test

5 Deep Learning for Computer Vision(PyTorch)

06.01. 1. PyTorch Kirish (Xususiyatlar)
06.02. 2. Indekslash (Indexing)
06.03. 3. (Slicing)
06.04. 4. PyTorchning asosiy operatsiyalari(Basic PyTorch Operations)
06.05. 5. Aggregatsiya funksiyalari(Aggregation functions)
06.06. 6. Regressiya va klassifikatsiya( Regression and Classification)
06.07. 7. Regressiya uchun xatolik funksiyalari (Loss functions for regression)
06.08. 8. Chiziqli regressiya (Gradient Descent)( Linear Regression Gradient Descent)
06.09. 9. Chiziqli model(Linear model)
06.10. 10. Xato funksiyasi(loss function)
06.11. 11. Optimallashtiruvchi(OPTIMIZER)
06.12. 12. Ko'p chiziqli regressiya(Multiple Linear Regression )
06.13. 13. Ko'p chiziqli regressiya o'qitish (Multiple Linear Regression training loop)
06.14. 14. Activation Functions
06.15. 15. Chiziqli bo'lmagan regressiya(Non-Linear Regression)
06.16. 16. Klassifikatsiya
06.17. 17. Dataset yaratish (make blobs)
06.18. 18. Datasetni o'qitish va baholash uchun ajratish (train test split)
06.19. 19. Klassifikatsiyani o'rgatish(classification train)
06.20. 20. O'qitishning aniqligi (Training accuracy)
06.21. 21. Natijalarni tasvirlash (train function plot loss)
06.22. 22. 07 MNIST Homework
06.23. 23. Maʼlumotlar toʻplami(datasets)
06.24. 24. Dataloader
06.25. 25. Dataset va Dataloader o'qitish ( Dataset and Dataloader train)
06.26. 26. Dataset va Dataloader o'qitish va baholash ( Dataset and Dataloader train)
06.27. 27. CNN Kirish
06.28. 28. TorchVision Transforms
06.29. 29. TorchVision Transforms final
06.30. 30. Transform COMPOSE
06.31. 31. Dataset LeNet
06.32. 32. LeNet kassifikatsiya(Train LeNet)
06.33. 33. GPU bilan o'qitish
06.34. 34. Resnet50 (cat and Dog)
06.35. 35. pre-trained model VGG11
06.36. 02 yolov5
06.37. 03 deeplab
06.38. Bo'lim bo'yicha yakuniy test

6 Kirish

07.01. Mohirdevga xush kelibsiz
07.02. Darslarni kompyuterda ko'rish
07.03. Darslarni telefonda ko'rish
07.04. Ommaviy oferta bilan tanishib chiqing
07.05. Yopiq guruhga kirish
07.06. Savol so'rash bo'yicha qo'llanma

Ommaviy ofertani ko'rish