[FCSNEW.NET] Udemy - Complete Computer Vision Bootcamp With PyTorch & Tensorflow

Creation Time	Oct. 13, 2025, 2:16 p.m.
Last Access Time	Oct. 13, 2025, 6:17 p.m.
File Size	28.3 GB
Keywords	Complete With - Udemy PyTorch Computer Tensorflow NET Bootcamp FCSNEW Vision
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Total Files	560
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05. computer vision (Open CV With Python)/19. Image Segmentation Using openCV.mp4 658.3 MB
06. PyTorch/16. CNN Training Using a Custom Dataset.mp4 535.3 MB
02. Python Prerequisites/37. Pandas-DataFrame And Series.mp4 532.6 MB
02. Python Prerequisites/36. Numpy In Python.mp4 520.4 MB
02. Python Prerequisites/38. Data Manipulation With Pandas And Numpy.mp4 447.0 MB
05. computer vision (Open CV With Python)/20. Haar Cascade for face detection.mp4 419.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/6. Vanishing Gradient Problem and Sigmoid.mp4 399.2 MB
11. Image Segmentation/7. Implementing Custom Unet Training.mp4 396.0 MB
02. Python Prerequisites/12. Sets In Python.mp4 393.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/3. ANN intuition and Working.mov.mp4 386.5 MB
02. Python Prerequisites/9. Loops In Python.mp4 376.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/4. Back Propogation and Weight Updation.mp4 359.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/17. Loss Function Classification Problem.mp4 358.0 MB
06. PyTorch/12. Create Linear Regression model with Pytorch components.mp4 353.4 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/1. Perceptron Intuition.mp4 326.9 MB
11. Image Segmentation/5. Fully Convolutional Networks (FCNs).mp4 325.0 MB
10. Basics of Object Detection/11. Custom Object Detection with YOLOv11.mp4 307.4 MB
02. Python Prerequisites/8. Conditional Statements(if,elif,else).mp4 307.1 MB
06. PyTorch/22. Implementing gradio app inference backend.mp4 306.9 MB
02. Python Prerequisites/13. Dictionaries In Python.mp4 298.8 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/16. Regression Cost Function.mp4 285.7 MB
11. Image Segmentation/8. Mask-RCNN.mp4 275.5 MB
05. computer vision (Open CV With Python)/11. Affine.mp4 275.5 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/32. Convolution Operatuin In CNN.mp4 275.1 MB
05. computer vision (Open CV With Python)/6. image Resizing, Scaling and interpolation.mp4 274.9 MB
02. Python Prerequisites/39. Reading Data From Various Data Source Using Pandas.mp4 272.3 MB
11. Image Segmentation/9. Training Yolov11 Instance Segmentation.mp4 271.0 MB
02. Python Prerequisites/5. Variables In Python.mp4 267.7 MB
06. PyTorch/14. Understanding components of custom data loader in pytorch.mp4 266.8 MB
02. Python Prerequisites/40. Logging Practical Implementation In Python.mp4 254.2 MB
06. PyTorch/15. Defining custom Image Dataset loader and usage.mp4 248.4 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/8. Sigmoid Activation Function part -2.mp4 234.8 MB
10. Basics of Object Detection/12. Custom Object Detection with Detectron2.mp4 233.4 MB
03. Introduction To Deep Learning/2. Why Deep Learning is Becoming Popular.mp4 228.4 MB
02. Python Prerequisites/16. More Coding Examples With Functions.mp4 224.2 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/5. Chain Rule Of Derivatives.mp4 223.7 MB
02. Python Prerequisites/4. Python Basics- Syntax and Semantics.mp4 221.1 MB
06. PyTorch/7. Tensor Manuplation.mp4 214.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/28. Dropout Layers.mp4 213.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/22. SGD with Momentum.mp4 211.5 MB
10. Basics of Object Detection/2. Object Detection Metrics.mp4 208.1 MB
06. PyTorch/11. Understanding Pytorch neural network components.mp4 206.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/19. Gradient Descent Optimizers.mp4 206.7 MB
02. Python Prerequisites/24. Exception Handling.mp4 204.3 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/27. Weight Initialisation Techniques.mp4 201.5 MB
05. computer vision (Open CV With Python)/4. Exploring Color Space.mp4 199.3 MB
07. Deep Dive Visualizing CNNs/1. Image Understanding with CNNs vs ANNs.mp4 198.7 MB
05. computer vision (Open CV With Python)/18. Contours.mp4 196.7 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/13. Softmax for Multiclass Classification.mp4 194.4 MB
02. Python Prerequisites/28. Encapsulation In OOPS.mp4 187.0 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/10. Relu Activation Function.mp4 184.5 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/35. Max, Min and Average Pooling.mp4 182.4 MB
02. Python Prerequisites/25. Classes And Objects In Python.mp4 179.2 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/21. Mini Batch With SGD.mp4 178.6 MB
02. Python Prerequisites/15. Getting Started With Functions.mp4 177.2 MB
10. Basics of Object Detection/4. Getting started with YOLO.mp4 177.1 MB
02. Python Prerequisites/35. Function Copy,Closures And Decorators.mp4 176.7 MB
05. computer vision (Open CV With Python)/12. Image FIlters.mp4 176.6 MB
05. computer vision (Open CV With Python)/14. Edge Detection Using Sobel, Canny & Laplacian.mp4 173.7 MB
11. Image Segmentation/1. Introduction to Image Segmentation.mp4 173.2 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/26. Exploding Gradient Problem.mp4 169.6 MB
02. Python Prerequisites/14. Tuples In Python.mp4 168.7 MB
02. Python Prerequisites/7. Operators In Python.mp4 167.6 MB
06. PyTorch/13. Multi Class classification with pytorch using custom neural networks.mp4 165.2 MB
02. Python Prerequisites/26. Inheritance In OOPS.mp4 161.6 MB
02. Python Prerequisites/27. Polymorphism In OOPS.mp4 157.7 MB
02. Python Prerequisites/2. Anaconda Installation.mp4 156.2 MB
05. computer vision (Open CV With Python)/3. Working with the video Files.mp4 155.4 MB
05. computer vision (Open CV With Python)/16. Histogram Equalization.mp4 155.0 MB
05. computer vision (Open CV With Python)/5. Color Thresholding.mp4 151.5 MB
10. Basics of Object Detection/1. What is Object Detection.mp4 148.7 MB
05. computer vision (Open CV With Python)/7. Flip, Rotate and Crop Images.mp4 146.8 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/29. CNN Introduction.mp4 146.5 MB
03. Introduction To Deep Learning/1. Introduction.mp4 146.4 MB
02. Python Prerequisites/21. Standard Library Overview.mp4 144.5 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/23. Adagard.mp4 144.2 MB
08. Image Classification/4. LeNet with Pytorch.mp4 141.8 MB
02. Python Prerequisites/3. Getting Started With VS Code.mp4 141.7 MB
06. PyTorch/10. Stack Operation.mp4 140.5 MB
10. Basics of Object Detection/10. FASTER RCNN with Pytorch Implementation.mp4 140.2 MB
08. Image Classification/17. ResNet Architecture.mp4 140.1 MB
02. Python Prerequisites/42. Logging With a Real World Examples.mp4 137.6 MB
10. Basics of Object Detection/5. Getting started with Detectron2.mp4 137.2 MB
07. Deep Dive Visualizing CNNs/2. CNN Explainer.mp4 136.8 MB
02. Python Prerequisites/32. Custom Exception Handling.mp4 136.1 MB
02. Python Prerequisites/22. File Operation In Python.mp4 135.9 MB
02. Python Prerequisites/20. Import Modules And Package In Python.mp4 135.4 MB
08. Image Classification/6. AlexNet with Keras.mp4 135.3 MB
06. PyTorch/19. Tools to create interactive demos.mp4 135.2 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/36. Flattening and Fully Connected Layers.mp4 134.8 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/34. Operation Of CNN Vs ANN.mp4 133.1 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/30. Human Brain V CNN.mp4 131.0 MB
10. Basics of Object Detection/9. FASTER RCNN.mp4 129.7 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/20. SGD.mp4 129.1 MB
02. Python Prerequisites/6. Basic Datatypes In Python.mp4 126.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/31. All you need to know about Images.mp4 121.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/2. Adv and Diadvantaes of Perceptron.mp4 121.6 MB
07. Deep Dive Visualizing CNNs/5. Building Your Own Filters.mp4 116.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/7. Sigmoid Activation Function.mp4 116.3 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/15. Loss Function Vs Cost Function.mp4 116.1 MB
07. Deep Dive Visualizing CNNs/4. CNN Filters.mp4 115.1 MB
11. Image Segmentation/6. UNet.mp4 113.4 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/25. Adam Optimiser.mp4 113.4 MB
09. Data Augmentation/2. Data Augmentation with Albumentations.mp4 112.9 MB
05. computer vision (Open CV With Python)/17. CLAHE.mp4 111.3 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/24. RMSPROP.mp4 109.7 MB
06. PyTorch/6. Tensor data types.mp4 108.3 MB
08. Image Classification/20. Resnet Transfer Learning.mp4 107.9 MB
06. PyTorch/1. Introduction PyTorch.mp4 106.9 MB
06. PyTorch/3. indexing Tensors.mp4 105.6 MB
08. Image Classification/7. AlexNet with Pytorch.mp4 105.4 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/33. Padding In CNN.mp4 104.9 MB
08. Image Classification/12. VGG Transfer Learning.mp4 103.9 MB
08. Image Classification/13. Inception Architecture.mp4 102.9 MB
08. Image Classification/16. Inception Transfer Learning.mp4 102.7 MB
11. Image Segmentation/10. Testing Yolov11 Instance Segmentation.mp4 102.2 MB
05. computer vision (Open CV With Python)/15. Calculating and Plotting Histogram.mp4 102.2 MB
06. PyTorch/4. Using Random Numbers to create noise image.mp4 99.9 MB
06. PyTorch/9. View and Reshape Operation.mp4 98.0 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/9. Tanh Activation Function.mp4 98.0 MB
07. Deep Dive Visualizing CNNs/7. CNN Parameter Calculations.mp4 97.7 MB
05. computer vision (Open CV With Python)/13. Applying Blur filters Average, Gaussian, Median.mp4 97.2 MB
08. Image Classification/8. VGG Architecture.mp4 96.7 MB
06. PyTorch/2. Introduction to Tensors.mp4 96.4 MB
07. Deep Dive Visualizing CNNs/3. Visualization with Tensorspace.mp4 92.6 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/14. Which Activation Function To Apply When.mp4 91.7 MB
05. computer vision (Open CV With Python)/9. Drawing lines and shapes using opencv.mp4 90.2 MB
11. Image Segmentation/3. UpsamplingTransposed Convolution.mp4 89.4 MB
10. Basics of Object Detection/6. Object Detection Architectures.mp4 89.0 MB
07. Deep Dive Visualizing CNNs/8. Receptive Fields.mp4 88.9 MB
11. Image Segmentation/4. Segmentation Loss Functions.mp4 88.5 MB
02. Python Prerequisites/41. Logging With Multiple Loggers.mp4 88.4 MB
02. Python Prerequisites/34. Generators In Python.mp4 86.9 MB
05. computer vision (Open CV With Python)/2. Reading and Writing Images.mp4 85.2 MB
08. Image Classification/3. LeNet with Keras.mp4 85.0 MB
06. PyTorch/17. Understanding Components of an Application.mp4 85.0 MB
08. Image Classification/20. Fruits dataset.zip 84.8 MB
01. Introduction/1. Welcome to the Course.mp4 83.3 MB
11. Image Segmentation/2. Downsampling.mp4 83.2 MB
02. Python Prerequisites/18. Map Functions In Python.mp4 82.4 MB
02. Python Prerequisites/11. Preactical Exmaples Of List.mp4 82.2 MB
07. Deep Dive Visualizing CNNs/6. Feature Map Size Calculation.mp4 81.4 MB
09. Data Augmentation/1. What is Data Augmentation.mp4 81.3 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/11. Leaky Relu and Parametric Relu.mp4 79.3 MB
06. PyTorch/8. Matrix Aggregation.mp4 79.2 MB
10. Basics of Object Detection/8. FAST RCNN.mp4 79.0 MB
08. Image Classification/1. What is Image Classification.mp4 78.6 MB
02. Python Prerequisites/31. Operator Overloading In Python.mp4 77.4 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/37. CNN Example with RGB.mp4 76.9 MB
10. Basics of Object Detection/7. RCNN.mp4 76.7 MB
02. Python Prerequisites/23. Working With File Paths.mp4 73.8 MB
06. PyTorch/24. Deploying gradio app on hugging face space.mp4 73.3 MB
02. Python Prerequisites/29. Abstraction In OOPS.mp4 72.2 MB
06. PyTorch/20. Hosting platform.mp4 70.5 MB
02. Python Prerequisites/19. Filter Function In Python.mp4 70.4 MB
02. Python Prerequisites/10. List and List Comprehension In Python.mp4 69.8 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/12. ELU Activation Function.mp4 69.0 MB
02. Python Prerequisites/30. Magic Methods In Python.mp4 68.5 MB
02. Python Prerequisites/17. Python Lambda Functions.mp4 68.2 MB
05. computer vision (Open CV With Python)/10. Adding Text to Image.mp4 67.5 MB
08. Image Classification/5. AlexNet Architecture.mp4 67.4 MB
08. Image Classification/10. VGG Pretrained Keras.mp4 65.6 MB
08. Image Classification/2. LeNet Architecture.mp4 65.5 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/18. Which Loss Function To Use When.mp4 62.1 MB
09. Data Augmentation/3. Data Augmentation with Imgaug.mp4 58.6 MB
06. PyTorch/23. Setting hugging face space.mp4 58.5 MB
06. PyTorch/21. Setting up gradio app in local space.mp4 54.5 MB
10. Basics of Object Detection/3. What are Bounding Boxes.mp4 50.5 MB
02. Python Prerequisites/33. Iterators In Python.mp4 47.5 MB
05. computer vision (Open CV With Python)/1. Introduction to OpenCV.mp4 46.9 MB
08. Image Classification/14. Inception Pretrained Keras.mp4 45.8 MB
08. Image Classification/11. VGG Pretrained Pytorch.mp4 42.4 MB
06. PyTorch/5. Tensors of Zero's and One's.mp4 35.4 MB
08. Image Classification/15. Inception Pretrained Pytorch.mp4 35.3 MB
08. Image Classification/9. Transfer Learning vs Pretrained.mp4 34.0 MB
10. Basics of Object Detection/5. Getting_Started_with_Detectron2_Object_Detection.ipynb 33.4 MB
06. PyTorch/22. 022. Implementing gradio app inference backend(gradio-app-1-chkpt-22).zip 31.3 MB
06. PyTorch/16. 016-CNN-Training-Using-a-Custom-Dataset.zip 31.2 MB
06. PyTorch/18. What is Deployment.mp4 30.2 MB
08. Image Classification/19. Resnet Pretrained Pytorch.mp4 26.0 MB
08. Image Classification/18. Resnet Pretrained Keras.mp4 21.9 MB
05. computer vision (Open CV With Python)/8. Understanding Coordinate system in openCV.mp4 21.8 MB
05. computer vision (Open CV With Python)/3. 003. Working_with_video_files.zip 8.8 MB
07. Deep Dive Visualizing CNNs/1. Understanding of images with Visualization.pdf 8.4 MB
05. computer vision (Open CV With Python)/2. 002. Reading_and_writing_images.zip 6.6 MB
05. computer vision (Open CV With Python)/11. 011. Affine and Perspective Transformation.zip 5.1 MB
10. Basics of Object Detection/12. Custom_Dataset_Training_with_Detectron2.ipynb 5.0 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/29. 30-38 CNN.pdf 5.0 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/6. 8-15 Activation functions.pdf 4.7 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/19. 20-26 Optimizers.pdf 4.2 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/3. 5-8 Deep LEarning.pdf 4.2 MB
07. Deep Dive Visualizing CNNs/5. Building Your Custom Filters.ipynb 4.1 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/15. 16-19 Loss Functions.pdf 3.5 MB
03. Introduction To Deep Learning/1. 1-4 Deep learnng.pdf 3.1 MB
05. computer vision (Open CV With Python)/20. 020. Haar Cascade for face detection (1).zip 3.1 MB
05. computer vision (Open CV With Python)/19. 019. Image Segmentation Using openCV (1).zip 2.9 MB
05. computer vision (Open CV With Python)/7. 007. Flip, Rotate and Crop Images.zip 2.3 MB
11. Image Segmentation/8. 008-Mask-RCNN.pdf 2.2 MB
05. computer vision (Open CV With Python)/6. 006. Image Resizing, Scaling and interpolation.zip 2.1 MB
09. Data Augmentation/2. Data_Augmenation_with_Albumentations.ipynb 2.0 MB
11. Image Segmentation/1. 001-Introduction to image segmentation.pdf 2.0 MB
10. Basics of Object Detection/1. What is Object Detection.pdf 1.9 MB
05. computer vision (Open CV With Python)/11. 011. Affine and Perspective Transformation.pdf 1.9 MB
05. computer vision (Open CV With Python)/16. 016. Histogram Equalization.zip 1.9 MB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/27. 27-8 Weight initialization Techniques.pdf 1.9 MB
05. computer vision (Open CV With Python)/4. 004. Exploring_Color_Space (1).zip 1.8 MB
08. Image Classification/8. VGG CNN Architecture .pdf 1.8 MB
10. Basics of Object Detection/9. Faster RCNN.pdf 1.8 MB
05. computer vision (Open CV With Python)/6. 006. Image Resizing, Scaling and interpolation (1).zip 1.7 MB
05. computer vision (Open CV With Python)/17. 017. CLAHE.zip 1.7 MB
05. computer vision (Open CV With Python)/14. 014. Edge Detection Using Sobel, Canny & Laplacian_pdf.zip 1.6 MB
11. Image Segmentation/5. 005-Fully Convolutional Networks (FCNs).pdf 1.6 MB
05. computer vision (Open CV With Python)/19. 019. Image Segmentation Using openCV.zip 1.5 MB
08. Image Classification/17. Resnet Architecture .pdf 1.5 MB
10. Basics of Object Detection/7. RCNN.pdf 1.4 MB
05. computer vision (Open CV With Python)/12. 012. Image FIlters (1).zip 1.4 MB
08. Image Classification/13. Googlenet CNN Architecture.pdf 1.4 MB
08. Image Classification/2. LeNet-5 CNN Architecture .pdf 1.3 MB
10. Basics of Object Detection/8. Fast RCNN.pdf 1.2 MB
06. PyTorch/20. 020. Hosting platform.pdf 1.2 MB
10. Basics of Object Detection/10. Faster_RCNN_with_Pytorch.ipynb 1.2 MB
10. Basics of Object Detection/3. Bounding Boxes.pdf 1.1 MB
08. Image Classification/1. What is Image Classification.pdf 1.1 MB
11. Image Segmentation/4. 004-Segmentation Loss Functions.pdf 1.0 MB
05. computer vision (Open CV With Python)/14. 014. Edge Detection Using Sobel, Canny & Laplacian.zip 1.0 MB
10. Basics of Object Detection/11. Custom_Dataset_Training_with_YOLOv11.ipynb 1.0 MB
05. computer vision (Open CV With Python)/5. 005. Color Thresholding (1).zip 1.0 MB
11. Image Segmentation/6. 006-Unet.pdf 1.0 MB
05. computer vision (Open CV With Python)/16. 016. Histogram Equalization (1).zip 1005.3 KB
05. computer vision (Open CV With Python)/3. 003. Working_with_video_files (1).zip 1004.6 KB
06. PyTorch/17. 017. Understanding Components of an Application.pdf 973.8 KB
10. Basics of Object Detection/6. Object Detection Architectures .pdf 955.1 KB
06. PyTorch/9. 009-View-and-reshape.zip 943.3 KB
06. PyTorch/9. 009-View-and-reshape.pdf 943.1 KB
05. computer vision (Open CV With Python)/17. 017. CLAHE.pdf 940.2 KB
11. Image Segmentation/9. 009-Training Yolov11 Instance Segmentation.pdf 939.0 KB
08. Image Classification/5. AlexNet CNN Architecture.pdf 906.3 KB
06. PyTorch/15. 015. Defining custom Image Dataset loader and usage.pdf 897.8 KB
06. PyTorch/16. 016. CNN Training Using a Custom Dataset.pdf 897.4 KB
07. Deep Dive Visualizing CNNs/7. CNN Parameters Calculation.pdf 893.5 KB
11. Image Segmentation/3. 003-Transposed convolution.pdf 891.5 KB
06. PyTorch/19. 019. Tools to create interactive demos.pdf 887.2 KB
05. computer vision (Open CV With Python)/7. 007. Flip, Rotate and Crop Images (1).zip 884.8 KB
09. Data Augmentation/3. Data_Augmentation_with_IMGAUG.ipynb 874.9 KB
05. computer vision (Open CV With Python)/5. 005. Color Thresholding.zip 866.4 KB
06. PyTorch/11. 011-Understanding-Pytorch-neural-network-components.pdf 862.3 KB
07. Deep Dive Visualizing CNNs/8. Receptive Fields in CNN.pdf 848.7 KB
06. PyTorch/10. 010-Stack-Operation.zip 846.8 KB
06. PyTorch/10. 010-Stack-Operation.pdf 846.6 KB
06. PyTorch/18. 018. What is Deployment.pdf 843.6 KB
11. Image Segmentation/2. 002-Downsampling.pdf 825.8 KB
05. computer vision (Open CV With Python)/18. 018. Contours (1).zip 817.8 KB
05. computer vision (Open CV With Python)/4. 004. Exploring_Color_Space.zip 813.6 KB
08. Image Classification/20. Resnet Transfer Learning Pytorch.ipynb 787.0 KB
05. computer vision (Open CV With Python)/8. 008. Understanding Coordinate system in openCV.pdf 780.0 KB
08. Image Classification/16. InceptionV3_Transfer_Learning_Keras_CIFAR10.ipynb 760.7 KB
04. Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/28. 29-Dropout Layer.pdf 760.1 KB
06. PyTorch/4. 004-Using Random Numbers to create noise image .zip 759.8 KB
08. Image Classification/14. Inception Pretrained.ipynb 754.3 KB
05. computer vision (Open CV With Python)/13. 013. Applying Blur filters Average, Gaussian, Median.zip 679.6 KB
08. Image Classification/18. Resnet Pretrained Keras.ipynb 654.8 KB
09. Data Augmentation/1. Data Augmentation(DA).pdf 620.8 KB
05. computer vision (Open CV With Python)/13. 013. Applying Blur filters Average, Gaussian, Median (1).zip 585.1 KB
05. computer vision (Open CV With Python)/12. 012. Image FIlters.zip 570.4 KB
05. computer vision (Open CV With Python)/18. 018. Contours.zip 558.8 KB
02. Python Prerequisites/1. Complete-Python-Bootcamp-main.zip 554.2 KB
02. Python Prerequisites/3. Complete-Python-Bootcamp-main.zip 554.2 KB
07. Deep Dive Visualizing CNNs/6. Feature Map Size Calculation .pdf 550.3 KB
05. computer vision (Open CV With Python)/15. 015. Calculating and Plotting Histograms (1).zip 472.1 KB
05. computer vision (Open CV With Python)/2. 002. Reading_and_writing_images (1).zip 471.6 KB
08. Image Classification/12. VGG Transfer Learning Pytorch.ipynb 440.3 KB
08. Image Classification/19. Resnet Pretrained Pytorch.ipynb 422.1 KB
11. Image Segmentation/8. 008-Mask-RCNN.zip 413.1 KB
05. computer vision (Open CV With Python)/9. 009. Drawing lines and shapes using opencv.zip 408.9 KB
08. Image Classification/15. Inception Pytorch Pretrained.ipynb 408.5 KB
07. Deep Dive Visualizing CNNs/4. CNN Filters.pdf 406.9 KB
08. Image Classification/10. VGG Keras Pretrained Model.ipynb 392.0 KB
08. Image Classification/9. Transfer Learning vs Pretrained .pdf 385.9 KB
08. Image Classification/11. VGG Pretrained Pytorch.ipynb 364.3 KB
05. computer vision (Open CV With Python)/15. 015. Calculating and Plotting Histograms.zip 304.7 KB
06. PyTorch/15. 015-Defining-custom-Image-Dataset-loader-and-usage.zip 155.7 KB
05. computer vision (Open CV With Python)/19. Image Segmentation Using openCV.vtt 122.9 KB
11. Image Segmentation/9. 009-Training Yolov11 Instance Segmentation.zip 119.4 KB
08. Image Classification/6. AlexNet _ Keras.ipynb 108.1 KB
06. PyTorch/16. CNN Training Using a Custom Dataset.vtt 104.4 KB
05. computer vision (Open CV With Python)/9. 009. Drawing lines and shapes using opencv (1).zip 90.4 KB
08. Image Classification/4. LeNet5 Pytorch.ipynb 89.3 KB
05. computer vision (Open CV With Python)/20. Haar Cascade for face detection.vtt 70.0 KB
08. Image Classification/7. AlexNet Pytorch.ipynb 68.5 KB
06. PyTorch/12. Create Linear Regression model with Pytorch components.vtt 64.2 KB
11. Image Segmentation/7. Implementing Custom Unet Training.vtt 62.9 KB
11. Image Segmentation/5. Fully Convolutional Networks (FCNs).vtt 59.7 KB
05. computer vision (Open CV With Python)/11. Affine.vtt 55.5 KB
06. PyTorch/7. Tensor Manuplation.vtt 55.1 KB
02. Python Prerequisites/10. List and List Comprehension In Python.vtt 52.5 KB
07. Deep Dive Visualizing CNNs/5. Build Your Custom Filters.pdf 51.9 KB
02. Python Prerequisites/13. Dictionaries In Python.vtt 50.8 KB
05. computer vision (Open CV With Python)/10. 010. Adding Text to images.zip 48.5 KB
06. PyTorch/14. Understanding components of custom data loader in pytorch.vtt 48.1 KB
06. PyTorch/11. Understanding Pytorch neural network components.vtt 47.4 KB
05. computer vision (Open CV With Python)/18. Contours.vtt 46.1 KB
06. PyTorch/15. Defining custom Image Dataset loader and usage.vtt 44.1 KB
02. Python Prerequisites/37. Pandas-DataFrame And Series.vtt 42.9 KB
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