Udemy - Complete Computer Vision Bootcamp With PyTorch & Tensorflow (1.2025)

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Udemy - Complete Computer Vision Bootcamp With PyTorch & Tensorflow (1.2025)

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收录时间：2025-07-18
最近下载：2025-10-02

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文件列表

  • 5 - computer vision (Open CV With Python)/19 -Image Segmentation Using openCV.mp4 690.3 MB
  • 6 - PyTorch/16 -CNN Training Using a Custom Dataset.mp4 561.3 MB
  • 2 - Python Prerequisites/36 -Pandas-DataFrame And Series.mp4 558.5 MB
  • 2 - Python Prerequisites/35 -Numpy In Python.mp4 545.7 MB
  • 2 - Python Prerequisites/37 -Data Manipulation With Pandas And Numpy.mp4 468.7 MB
  • 5 - computer vision (Open CV With Python)/20 -Haar Cascade for face detection.mp4 440.3 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/6 -Vanishing Gradient Problem and Sigmoid.mp4 418.6 MB
  • 2 - Python Prerequisites/11 -Sets In Python.mp4 412.7 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/3 -ANN intuition and Working.mov.mp4 405.2 MB
  • 2 - Python Prerequisites/8 -Loops In Python.mp4 395.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/4 -Back Propogation and Weight Updation.mp4 377.4 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/17 -Loss Function Classification Problem.mp4 375.4 MB
  • 6 - PyTorch/12 -Create Linear Regression model with Pytorch components.mp4 370.6 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/1 -Perceptron Intuition.mp4 342.8 MB
  • 11 - Image Segmentation/5 -Fully Convolutional Networks (FCNs).mp4 340.8 MB
  • 10 - Basics of Object Detection/11 -Custom Object Detection with YOLOv11.mp4 322.3 MB
  • 2 - Python Prerequisites/7 -Conditional Statements(if,elif,else).mp4 322.0 MB
  • 6 - PyTorch/22 -Implementing gradio app inference backend.mp4 321.8 MB
  • 2 - Python Prerequisites/12 -Dictionaries In Python.mp4 313.3 MB
  • 2 - Python Prerequisites/9 -List and List Comprehension In Python.mp4 300.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/16 -Regression Cost Function.mp4 299.6 MB
  • 5 - computer vision (Open CV With Python)/11 -Affine.mp4 288.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/32 -Convolution Operatuin In CNN.mp4 288.5 MB
  • 5 - computer vision (Open CV With Python)/6 -image Resizing, Scaling and interpolation.mp4 288.3 MB
  • 2 - Python Prerequisites/38 -Reading Data From Various Data Source Using Pandas.mp4 285.5 MB
  • 2 - Python Prerequisites/4 -Variables In Python.mp4 280.7 MB
  • 6 - PyTorch/14 -Understanding components of custom data loader in pytorch.mp4 279.8 MB
  • 2 - Python Prerequisites/39 -Logging Practical Implementation In Python.mp4 266.5 MB
  • 6 - PyTorch/15 -Defining custom Image Dataset loader and usage.mp4 260.5 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/8 -Sigmoid Activation Function part -2.mp4 246.2 MB
  • 10 - Basics of Object Detection/12 -Custom Object Detection with Detectron2.mp4 244.7 MB
  • 3 - Introduction To Deep Learning/2 -Why Deep Learning is Becoming Popular.mp4 239.5 MB
  • 2 - Python Prerequisites/15 -More Coding Examples With Functions.mp4 235.1 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/5 -Chain Rule Of Derivatives.mp4 234.5 MB
  • 2 - Python Prerequisites/3 -Python Basics- Syntax and Semantics.mp4 231.8 MB
  • 6 - PyTorch/7 -Tensor Manuplation.mp4 225.0 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/28 -Dropout Layers.mp4 223.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/22 -SGD with Momentum.mp4 221.7 MB
  • 10 - Basics of Object Detection/2 -Object Detection Metrics.mp4 218.2 MB
  • 6 - PyTorch/11 -Understanding Pytorch neural network components.mp4 216.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/19 -Gradient Descent Optimizers.mp4 216.8 MB
  • 2 - Python Prerequisites/23 -Exception Handling.mp4 214.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/27 -Weight Initialisation Techniques.mp4 211.3 MB
  • 5 - computer vision (Open CV With Python)/4 -Exploring Color Space.mp4 208.9 MB
  • 7 - Deep Dive Visualizing CNNs/1 -Image Understanding with CNNs vs ANNs.mp4 208.4 MB
  • 5 - computer vision (Open CV With Python)/18 -Contours.mp4 206.3 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/13 -Softmax for Multiclass Classification.mp4 203.9 MB
  • 5 - computer vision (Open CV With Python)/14 -014.mp4 199.2 MB
  • 2 - Python Prerequisites/27 -Encapsulation In OOPS.mp4 196.1 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/10 -Relu Activation Function.mp4 193.4 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/35 -Max, Min and Average Pooling.mp4 191.2 MB
  • 2 - Python Prerequisites/24 -Classes And Objects In Python.mp4 187.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/21 -Mini Batch With SGD.mp4 187.2 MB
  • 2 - Python Prerequisites/14 -Getting Started With Functions.mp4 185.8 MB
  • 10 - Basics of Object Detection/4 -Getting started with YOLO.mp4 185.7 MB
  • 2 - Python Prerequisites/34 -Function Copy,Closures And Decorators.mp4 185.3 MB
  • 5 - computer vision (Open CV With Python)/12 -Image FIlters.mp4 185.2 MB
  • 5 - computer vision (Open CV With Python)/14 -Edge Detection Using Sobel, Canny & Laplacian.mp4 182.1 MB
  • 11 - Image Segmentation/1 -Introduction to Image Segmentation.mp4 181.6 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/26 -Exploding Gradient Problem.mp4 177.9 MB
  • 2 - Python Prerequisites/13 -Tuples In Python.mp4 176.9 MB
  • 2 - Python Prerequisites/6 -Operators In Python.mp4 175.8 MB
  • 6 - PyTorch/13 -Multi Class classification with pytorch using custom neural networks.mp4 173.2 MB
  • 2 - Python Prerequisites/25 -Inheritance In OOPS.mp4 169.5 MB
  • 2 - Python Prerequisites/26 -Polymorphism In OOPS.mp4 165.4 MB
  • 2 - Python Prerequisites/1 -Anaconda Installation.mp4 163.8 MB
  • 5 - computer vision (Open CV With Python)/2 -Working with the video Files.mp4 163.0 MB
  • 5 - computer vision (Open CV With Python)/16 -Histogram Equalization.mp4 162.5 MB
  • 5 - computer vision (Open CV With Python)/5 -Color Thresholding.mp4 158.9 MB
  • 10 - Basics of Object Detection/1 -What is Object Detection.mp4 155.9 MB
  • 5 - computer vision (Open CV With Python)/7 -Flip, Rotate and Crop Images.mp4 154.0 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/29 -CNN Introduction.mp4 153.6 MB
  • 3 - Introduction To Deep Learning/1 -Introduction.mp4 153.5 MB
  • 2 - Python Prerequisites/20 -Standard Library Overview.mp4 151.5 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/23 -Adagard.mp4 151.2 MB
  • 8 - Image Classification/4 -LeNet with Pytorch.mp4 148.7 MB
  • 2 - Python Prerequisites/2 -Getting Started With VS Code.mp4 148.6 MB
  • 6 - PyTorch/10 -Stack Operation.mp4 147.3 MB
  • 10 - Basics of Object Detection/10 -FASTER RCNN with Pytorch Implementation.mp4 147.0 MB
  • 8 - Image Classification/17 -ResNet Architecture.mp4 146.9 MB
  • 2 - Python Prerequisites/41 -Logging With a Real World Examples.mp4 144.3 MB
  • 10 - Basics of Object Detection/5 -Getting started with Detectron2.mp4 143.8 MB
  • 7 - Deep Dive Visualizing CNNs/2 -CNN Explainer.mp4 143.4 MB
  • 2 - Python Prerequisites/31 -Custom Exception Handling.mp4 142.8 MB
  • 2 - Python Prerequisites/21 -File Operation In Python.mp4 142.5 MB
  • 2 - Python Prerequisites/19 -Import Modules And Package In Python.mp4 142.0 MB
  • 8 - Image Classification/6 -AlexNet with Keras.mp4 141.9 MB
  • 6 - PyTorch/19 -Tools to create interactive demos.mp4 141.7 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/36 -Flattening and Fully Connected Layers.mp4 141.3 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/34 -Operation Of CNN Vs ANN.mp4 139.6 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/30 -Human Brain V CNN.mp4 137.3 MB
  • 10 - Basics of Object Detection/9 -FASTER RCNN.mp4 135.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/20 -SGD.mp4 135.3 MB
  • 2 - Python Prerequisites/5 -Basic Datatypes In Python.mp4 132.8 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/31 -All you need to know about Images.mp4 127.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/2 -Adv and Diadvantaes of Perceptron.mp4 127.5 MB
  • 7 - Deep Dive Visualizing CNNs/5 -Building Your Own Filters.mp4 122.3 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/7 -Sigmoid Activation Function.mp4 122.0 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/15 -Loss Function Vs Cost Function.mp4 121.8 MB
  • 7 - Deep Dive Visualizing CNNs/4 -CNN Filters.mp4 120.7 MB
  • 11 - Image Segmentation/6 -UNet.mp4 118.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/25 -Adam Optimiser.mp4 118.9 MB
  • 9 - Data Augmentation/2 -Data Augmentation with Albumentations.mp4 118.4 MB
  • 5 - computer vision (Open CV With Python)/17 -CLAHE.mp4 116.7 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/24 -RMSPROP.mp4 115.0 MB
  • 6 - PyTorch/6 -Tensor data types.mp4 113.6 MB
  • 8 - Image Classification/20 -Resnet Transfer Learning.mp4 113.1 MB
  • 6 - PyTorch/1 -Introduction PyTorch.mp4 112.1 MB
  • 6 - PyTorch/3 -indexing Tensors.mp4 110.8 MB
  • 8 - Image Classification/7 -AlexNet with Pytorch.mp4 110.5 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/33 -Padding In CNN.mp4 110.0 MB
  • 8 - Image Classification/12 -VGG Transfer Learning.mp4 109.0 MB
  • 8 - Image Classification/13 -Inception Architecture.mp4 107.9 MB
  • 8 - Image Classification/16 -Inception Transfer Learning.mp4 107.7 MB
  • 5 - computer vision (Open CV With Python)/15 -Calculating and Plotting Histogram.mp4 107.1 MB
  • 6 - PyTorch/4 -Using Random Numbers to create noise image.mp4 104.8 MB
  • 5 - computer vision (Open CV With Python)/13 -013.mp4 102.9 MB
  • 6 - PyTorch/9 -View and Reshape Operation.mp4 102.8 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/9 -Tanh Activation Function.mp4 102.7 MB
  • 7 - Deep Dive Visualizing CNNs/7 -CNN Parameter Calculations.mp4 102.4 MB
  • 5 - computer vision (Open CV With Python)/13 -Applying Blur filters Average, Gaussian, Median.mp4 101.9 MB
  • 8 - Image Classification/8 -VGG Architecture.mp4 101.4 MB
  • 6 - PyTorch/2 -Introduction to Tensors.mp4 101.1 MB
  • 7 - Deep Dive Visualizing CNNs/3 -Visualization with Tensorspace.mp4 97.0 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/14 -Which Activation Function To Apply When.mp4 96.2 MB
  • 5 - computer vision (Open CV With Python)/9 -Drawing lines and shapes using opencv.mp4 94.6 MB
  • 11 - Image Segmentation/3 -UpsamplingTransposed Convolution.mp4 93.8 MB
  • 10 - Basics of Object Detection/6 -Object Detection Architectures.mp4 93.3 MB
  • 7 - Deep Dive Visualizing CNNs/8 -Receptive Fields.mp4 93.2 MB
  • 11 - Image Segmentation/4 -Segmentation Loss Functions.mp4 92.8 MB
  • 2 - Python Prerequisites/40 -Logging With Multiple Loggers.mp4 92.7 MB
  • 2 - Python Prerequisites/33 -Generators In Python.mp4 91.2 MB
  • 5 - computer vision (Open CV With Python)/1 -Reading and Writing Images.mp4 89.3 MB
  • 8 - Image Classification/3 -LeNet with Keras.mp4 89.1 MB
  • 6 - PyTorch/17 -Understanding Components of an Application.mp4 89.1 MB
  • 11 - Image Segmentation/2 -Downsampling.mp4 87.3 MB
  • 2 - Python Prerequisites/17 -Map Functions In Python.mp4 86.4 MB
  • 2 - Python Prerequisites/10 -Preactical Exmaples Of List.mp4 86.2 MB
  • 7 - Deep Dive Visualizing CNNs/6 -Feature Map Size Calculation.mp4 85.3 MB
  • 9 - Data Augmentation/1 -What is Data Augmentation.mp4 85.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/11 -Leaky Relu and Parametric Relu.mp4 83.1 MB
  • 6 - PyTorch/8 -Matrix Aggregation.mp4 83.1 MB
  • 10 - Basics of Object Detection/8 -FAST RCNN.mp4 82.8 MB
  • 8 - Image Classification/1 -What is Image Classification.mp4 82.4 MB
  • 2 - Python Prerequisites/30 -Operator Overloading In Python.mp4 81.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/37 -CNN Example with RGB.mp4 80.7 MB
  • 10 - Basics of Object Detection/7 -RCNN.mp4 80.4 MB
  • 2 - Python Prerequisites/22 -Working With File Paths.mp4 77.4 MB
  • 6 - PyTorch/24 -Deploying gradio app on hugging face space.mp4 76.9 MB
  • 2 - Python Prerequisites/28 -Abstraction In OOPS.mp4 75.7 MB
  • 6 - PyTorch/20 -Hosting platform.mp4 74.0 MB
  • 2 - Python Prerequisites/18 -Filter Function In Python.mp4 73.8 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/12 -ELU Activation Function.mp4 72.4 MB
  • 2 - Python Prerequisites/29 -Magic Methods In Python.mp4 71.9 MB
  • 2 - Python Prerequisites/16 -Python Lambda Functions.mp4 71.5 MB
  • 5 - computer vision (Open CV With Python)/10 -Adding Text to Image.mp4 70.8 MB
  • 8 - Image Classification/5 -AlexNet Architecture.mp4 70.6 MB
  • 8 - Image Classification/10 -VGG Pretrained Keras.mp4 68.8 MB
  • 8 - Image Classification/2 -LeNet Architecture.mp4 68.7 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/18 -Which Loss Function To Use When.mp4 65.1 MB
  • 9 - Data Augmentation/3 -Data Augmentation with Imgaug.mp4 61.4 MB
  • 6 - PyTorch/23 -Setting hugging face space.mp4 61.3 MB
  • 6 - PyTorch/21 -Setting up gradio app in local space.mp4 57.2 MB
  • 10 - Basics of Object Detection/3 -What are Bounding Boxes.mp4 53.0 MB
  • 2 - Python Prerequisites/32 -Iterators In Python.mp4 49.8 MB
  • 5 - computer vision (Open CV With Python)/3 -Introduction openCv.mp4 49.2 MB
  • 8 - Image Classification/14 -Inception Pretrained Keras.mp4 48.0 MB
  • 8 - Image Classification/11 -VGG Pretrained Pytorch.mp4 44.5 MB
  • 6 - PyTorch/5 -Tensors of Zero's and One's.mp4 37.1 MB
  • 8 - Image Classification/15 -Inception Pretrained Pytorch.mp4 37.0 MB
  • 8 - Image Classification/9 -Transfer Learning vs Pretrained.mp4 35.6 MB
  • 10 - Basics of Object Detection/5 -Getting_Started_with_Detectron2_Object_Detection.ipynb 35.0 MB
  • 6 - PyTorch/22 -022.zip 32.8 MB
  • 6 - PyTorch/16 -016-CNN-Training-Using-a-Custom-Dataset.zip 32.8 MB
  • 6 - PyTorch/18 -What is Deployment.mp4 31.6 MB
  • 8 - Image Classification/19 -Resnet Pretrained Pytorch.mp4 27.3 MB
  • 8 - Image Classification/18 -Resnet Pretrained Keras.mp4 23.0 MB
  • 5 - computer vision (Open CV With Python)/8 -Understanding Coordinate system in openCV.mp4 22.9 MB
  • 7 - Deep Dive Visualizing CNNs/1 -Understanding of images with Visualization.pdf 8.8 MB
  • 5 - computer vision (Open CV With Python)/11 -011.zip 5.4 MB
  • 10 - Basics of Object Detection/12 -Custom_Dataset_Training_with_Detectron2.ipynb 5.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/29 -30-38 CNN.pdf 5.2 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/6 -8-15 Activation functions.pdf 4.9 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/19 -20-26 Optimizers.pdf 4.4 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/3 -5-8 Deep LEarning.pdf 4.4 MB
  • 7 - Deep Dive Visualizing CNNs/5 -Building Your Custom Filters.ipynb 4.3 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/15 -16-19 Loss Functions.pdf 3.6 MB
  • 3 - Introduction To Deep Learning/1 -1-4 Deep learnng.pdf 3.3 MB
  • 5 - computer vision (Open CV With Python)/19 -019.zip 3.1 MB
  • 9 - Data Augmentation/2 -Data_Augmenation_with_Albumentations.ipynb 2.1 MB
  • 11 - Image Segmentation/1 -001-Introduction to image segmentation.pdf 2.1 MB
  • 10 - Basics of Object Detection/1 -What is Object Detection.pdf 2.0 MB
  • 5 - computer vision (Open CV With Python)/11 -011.pdf 2.0 MB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/27 -27-8 Weight initialization Techniques.pdf 2.0 MB
  • 5 - computer vision (Open CV With Python)/4 -004.zip 1.9 MB
  • 8 - Image Classification/8 -VGG CNN Architecture.pdf 1.9 MB
  • 10 - Basics of Object Detection/9 -Faster RCNN.pdf 1.9 MB
  • 5 - computer vision (Open CV With Python)/6 -006.zip 1.8 MB
  • 5 - computer vision (Open CV With Python)/17 -017.zip 1.8 MB
  • 11 - Image Segmentation/5 -005-Fully Convolutional Networks (FCNs).pdf 1.7 MB
  • 8 - Image Classification/17 -Resnet Architecture.pdf 1.5 MB
  • 10 - Basics of Object Detection/7 -RCNN.pdf 1.5 MB
  • 8 - Image Classification/13 -Googlenet CNN Architecture.pdf 1.5 MB
  • 8 - Image Classification/2 -LeNet-5 CNN Architecture.pdf 1.4 MB
  • 10 - Basics of Object Detection/8 -Fast RCNN.pdf 1.3 MB
  • 6 - PyTorch/20 -020.pdf 1.3 MB
  • 10 - Basics of Object Detection/10 -Faster_RCNN_with_Pytorch.ipynb 1.2 MB
  • 10 - Basics of Object Detection/3 -Bounding Boxes.pdf 1.2 MB
  • 8 - Image Classification/1 -What is Image Classification.pdf 1.2 MB
  • 11 - Image Segmentation/4 -004-Segmentation Loss Functions.pdf 1.1 MB
  • 5 - computer vision (Open CV With Python)/14 -014.zip 1.1 MB
  • 10 - Basics of Object Detection/11 -Custom_Dataset_Training_with_YOLOv11.ipynb 1.1 MB
  • 5 - computer vision (Open CV With Python)/5 -005.zip 1.1 MB
  • 11 - Image Segmentation/6 -006-Unet.pdf 1.0 MB
  • 5 - computer vision (Open CV With Python)/16 -016.zip 1.0 MB
  • 5 - computer vision (Open CV With Python)/2 -003.zip 1.0 MB
  • 6 - PyTorch/17 -017.pdf 997.2 kB
  • 10 - Basics of Object Detection/6 -Object Detection Architectures.pdf 978.0 kB
  • 6 - PyTorch/9 -009-View-and-reshape.zip 965.9 kB
  • 6 - PyTorch/9 -009-View-and-reshape.pdf 965.7 kB
  • 5 - computer vision (Open CV With Python)/17 -017.pdf 962.8 kB
  • 8 - Image Classification/5 -AlexNet CNN Architecture.pdf 928.0 kB
  • 6 - PyTorch/15 -015.pdf 919.4 kB
  • 6 - PyTorch/16 -016.pdf 918.9 kB
  • 11 - Image Segmentation/3 -003-Transposed convolution.pdf 912.9 kB
  • 6 - PyTorch/19 -019.pdf 908.5 kB
  • 5 - computer vision (Open CV With Python)/7 -007.zip 906.0 kB
  • 9 - Data Augmentation/3 -Data_Augmentation_with_IMGAUG.ipynb 895.9 kB
  • 6 - PyTorch/11 -011-Understanding-Pytorch-neural-network-components.pdf 883.0 kB
  • 6 - PyTorch/10 -010-Stack-Operation.zip 867.2 kB
  • 6 - PyTorch/10 -010-Stack-Operation.pdf 867.0 kB
  • 6 - PyTorch/18 -018.pdf 863.9 kB
  • 11 - Image Segmentation/2 -002-Downsampling.pdf 845.6 kB
  • 5 - computer vision (Open CV With Python)/18 -018.zip 837.4 kB
  • 8 - Image Classification/20 -Resnet Transfer Learning Pytorch.ipynb 805.9 kB
  • 5 - computer vision (Open CV With Python)/8 -008.pdf 798.7 kB
  • 8 - Image Classification/16 -InceptionV3_Transfer_Learning_Keras_CIFAR10.ipynb 778.9 kB
  • 4 - Deep Learning-ANN, Optimizers, Loss Functions, Activation Functions,CNN Theory/28 -29-Dropout Layer.pdf 778.4 kB
  • 6 - PyTorch/4 -004-Using Random Numbers to create noise image.zip 778.0 kB
  • 8 - Image Classification/14 -Inception Pretrained.ipynb 772.4 kB
  • 8 - Image Classification/18 -Resnet Pretrained Keras.ipynb 670.6 kB
  • 5 - computer vision (Open CV With Python)/13 -013.zip 599.1 kB
  • 5 - computer vision (Open CV With Python)/12 -012.zip 584.1 kB
  • 2 - Python Prerequisites/1 -Complete-Python-Bootcamp-main.zip 567.5 kB
  • 2 - Python Prerequisites/2 -Complete-Python-Bootcamp-main.zip 567.5 kB
  • 5 - computer vision (Open CV With Python)/1 -002.zip 482.9 kB
  • 8 - Image Classification/12 -VGG Transfer Learning Pytorch.ipynb 450.9 kB
  • 8 - Image Classification/19 -Resnet Pretrained Pytorch.ipynb 432.3 kB
  • 5 - computer vision (Open CV With Python)/9 -009.zip 418.7 kB
  • 8 - Image Classification/15 -Inception Pytorch Pretrained.ipynb 418.3 kB
  • 7 - Deep Dive Visualizing CNNs/4 -CNN Filters.pdf 416.7 kB
  • 8 - Image Classification/10 -VGG Keras Pretrained Model.ipynb 401.4 kB
  • 8 - Image Classification/9 -Transfer Learning vs Pretrained.pdf 395.2 kB
  • 8 - Image Classification/11 -VGG Pretrained Pytorch.ipynb 373.0 kB
  • 5 - computer vision (Open CV With Python)/15 -015.zip 312.0 kB
  • 6 - PyTorch/15 -015-Defining-custom-Image-Dataset-loader-and-usage.zip 159.4 kB
  • 8 - Image Classification/6 -AlexNet _ Keras.ipynb 110.7 kB
  • 8 - Image Classification/4 -LeNet5 Pytorch.ipynb 91.4 kB
  • 8 - Image Classification/7 -AlexNet Pytorch.ipynb 70.1 kB
  • 7 - Deep Dive Visualizing CNNs/5 -Build Your Custom Filters.pdf 53.1 kB
  • 5 - computer vision (Open CV With Python)/10 -010.zip 49.6 kB
  • 6 - PyTorch/14 -014-Understanding-components-of-custom-data-loader-in-pytorch.zip 28.2 kB
  • 8 - Image Classification/3 -LeNet5 with MNIST Keras.ipynb 26.1 kB
  • 7 - Deep Dive Visualizing CNNs/7 -CNN Parameter Calculation.ipynb 15.3 kB
  • 10 - Basics of Object Detection/4 -Getting_Started_with_Yolov11.ipynb 13.2 kB
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