[FreeCourseSite.com] Udemy - Image Recognition for Beginners using CNN in R Studio

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[FreeCourseSite.com] Udemy - Image Recognition for Beginners using CNN in R Studio

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种子哈希：7f8038823bbfa70c8ea592a852ac652b2096801a
文件大小： 2.9G
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收录时间：2024-04-21
最近下载：2025-08-02

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文件列表

  • 12 - Saving and Restoring Models/28 - Saving Restoring Models and Using Callbacks.mp4 226.7 MB
  • 11 - R Complex ANN Architectures using Functional API/26 - Building Regression Model with Functional AP.mp4 137.5 MB
  • 9 - R Building and training the Model/23 - Building Compiling and Training.mp4 137.1 MB
  • 4 - Neural Networks Stacking cells to create network/16 - Back Propagation.mp4 128.1 MB
  • 8 - R Dataset for classification problem/21 - Data Normalization and TestTrain Split.mp4 117.2 MB
  • 20 - Transfer Learning in R/55 - Project Transfer Learning VGG16 Implementation.mp4 106.5 MB
  • 9 - R Building and training the Model/24 - Evaluating and Predicting.mp4 104.0 MB
  • 2 - Setting Up R Studio and R crash course/10 - Creating Barplots in R.mp4 101.4 MB
  • 17 - Project Creating CNN model from scratch/44 - Project in R Data Preprocessing.mp4 92.0 MB
  • 10 - The NeuralNets Package/25 - ANN with NeuralNets Package.mp4 88.5 MB
  • 2 - Setting Up R Studio and R crash course/6 - Packages in R.mp4 86.9 MB
  • 11 - R Complex ANN Architectures using Functional API/27 - Complex Architectures using Functional API.mp4 83.4 MB
  • 15 - Creating CNN model in R/38 - Creating Model Architecture.mp4 75.0 MB
  • 15 - Creating CNN model in R/40 - Model Performance.mp4 71.4 MB
  • 14 - CNN Basics/34 - Channels.mp4 71.1 MB
  • 15 - Creating CNN model in R/37 - Data Preprocessing.mp4 70.3 MB
  • 20 - Transfer Learning in R/56 - Project Transfer Learning VGG16 Performance.mp4 67.2 MB
  • 5 - Important concepts Common Interview questions/17 - Some Important Concepts.mp4 65.2 MB
  • 13 - Hyperparameter Tuning/29 - Hyperparameter Tuning.mp4 63.6 MB
  • 4 - Neural Networks Stacking cells to create network/15 - Gradient Descent.mp4 63.0 MB
  • 2 - Setting Up R Studio and R crash course/9 - Inputting data part 3 Importing from CSV or Text files.mp4 63.0 MB
  • 14 - CNN Basics/30 - CNN Introduction.mp4 59.5 MB
  • 18 - Project Data Augmentation for avoiding overfitting/48 - Project in R Data Augmentation.mp4 59.1 MB
  • 14 - CNN Basics/33 - Filters and Feature maps.mp4 55.3 MB
  • 17 - Project Creating CNN model from scratch/42 - Project Introduction.mp4 51.8 MB
  • 14 - CNN Basics/35 - PoolingLayer.mp4 49.1 MB
  • 17 - Project Creating CNN model from scratch/45 - CNN Project in R Structure and Compile.mp4 48.3 MB
  • 6 - Standard Model Parameters/18 - Hyperparameters.mp4 47.5 MB
  • 3 - Single Cells Perceptron and Sigmoid Neuron/12 - Perceptron.mp4 46.9 MB
  • 16 - Analyzing impact of Pooling layer/41 - Comparison Pooling vs Without Pooling in R.mp4 46.7 MB
  • 2 - Setting Up R Studio and R crash course/11 - Creating Histograms in R.mp4 44.0 MB
  • 2 - Setting Up R Studio and R crash course/7 - Inputting data part 1 Inbuilt datasets of R.mp4 42.7 MB
  • 4 - Neural Networks Stacking cells to create network/14 - Basic Terminologies.mp4 41.3 MB
  • 2 - Setting Up R Studio and R crash course/5 - Basics of R and R studio.mp4 40.7 MB
  • 2 - Setting Up R Studio and R crash course/3 - Installing R and R studio.mp4 37.4 MB
  • 3 - Single Cells Perceptron and Sigmoid Neuron/13 - Activation Functions.mp4 36.3 MB
  • 15 - Creating CNN model in R/39 - Compiling and training.mp4 33.8 MB
  • 14 - CNN Basics/32 - Padding.mp4 33.2 MB
  • 19 - Transfer Learning Basics/54 - Transfer Learning.mp4 31.5 MB
  • 2 - Setting Up R Studio and R crash course/8 - Inputting data part 2 Manual data entry.mp4 26.7 MB
  • 17 - Project Creating CNN model from scratch/46 - Project in R Training.mp4 25.8 MB
  • 18 - Project Data Augmentation for avoiding overfitting/49 - Project in R Validation Performance.mp4 24.9 MB
  • 17 - Project Creating CNN model from scratch/47 - Project in R Model Performance.mp4 24.3 MB
  • 7 - Tensorflow and Keras/20 - Installing Keras and Tensorflow.mp4 23.9 MB
  • 1 - Introduction/1 - Introduction.mp4 22.7 MB
  • 19 - Transfer Learning Basics/53 - GoogLeNet.mp4 22.4 MB
  • 19 - Transfer Learning Basics/50 - ILSVRC.mp4 22.0 MB
  • 2 - Setting Up R Studio and R crash course/4 - This is a milestone.mp4 21.7 MB
  • 14 - CNN Basics/31 - Stride.mp4 17.4 MB
  • 7 - Tensorflow and Keras/19 - Keras and Tensorflow.mp4 15.6 MB
  • 21 - Congratulations & about your certificate/57 - The final milestone.mp4 12.4 MB
  • 19 - Transfer Learning Basics/52 - VGG16NET.mp4 10.9 MB
  • 15 - Creating CNN model in R/36 - CNN on MNIST Fashion Dataset Model Architecture.mp4 7.7 MB
  • 19 - Transfer Learning Basics/51 - LeNET.mp4 7.3 MB
  • 4 - Neural Networks Stacking cells to create network/16 - Back Propagation English.vtt 22.8 kB
  • 12 - Saving and Restoring Models/28 - Saving Restoring Models and Using Callbacks English.vtt 19.7 kB
  • 2 - Setting Up R Studio and R crash course/10 - Creating Barplots in R English.vtt 16.8 kB
  • 9 - R Building and training the Model/23 - Building Compiling and Training English.vtt 14.9 kB
  • 2 - Setting Up R Studio and R crash course/6 - Packages in R English.vtt 13.4 kB
  • 2 - Setting Up R Studio and R crash course/5 - Basics of R and R studio English.vtt 13.1 kB
  • 20 - Transfer Learning in R/55 - Project Transfer Learning VGG16 Implementation English.vtt 13.0 kB
  • 5 - Important concepts Common Interview questions/17 - Some Important Concepts English.vtt 12.6 kB
  • 11 - R Complex ANN Architectures using Functional API/26 - Building Regression Model with Functional AP English.vtt 12.5 kB
  • 8 - R Dataset for classification problem/21 - Data Normalization and TestTrain Split English.vtt 11.7 kB
  • 4 - Neural Networks Stacking cells to create network/15 - Gradient Descent English.vtt 11.7 kB
  • 17 - Project Creating CNN model from scratch/44 - Project in R Data Preprocessing English.vtt 11.0 kB
  • 4 - Neural Networks Stacking cells to create network/14 - Basic Terminologies English.vtt 10.0 kB
  • 3 - Single Cells Perceptron and Sigmoid Neuron/12 - Perceptron English.vtt 9.5 kB
  • 9 - R Building and training the Model/24 - Evaluating and Predicting English.vtt 9.3 kB
  • 13 - Hyperparameter Tuning/29 - Hyperparameter Tuning English.vtt 9.1 kB
  • 6 - Standard Model Parameters/18 - Hyperparameters English.vtt 8.7 kB
  • 20 - Transfer Learning in R/56 - Project Transfer Learning VGG16 Performance English.vtt 8.2 kB
  • 11 - R Complex ANN Architectures using Functional API/27 - Complex Architectures using Functional API English.vtt 8.1 kB
  • 10 - The NeuralNets Package/25 - ANN with NeuralNets Package English.vtt 7.7 kB
  • 2 - Setting Up R Studio and R crash course/9 - Inputting data part 3 Importing from CSV or Text files English.vtt 7.7 kB
  • 3 - Single Cells Perceptron and Sigmoid Neuron/13 - Activation Functions English.vtt 7.6 kB
  • 14 - CNN Basics/30 - CNN Introduction English.vtt 7.2 kB
  • 2 - Setting Up R Studio and R crash course/11 - Creating Histograms in R English.vtt 7.0 kB
  • 14 - CNN Basics/33 - Filters and Feature maps English.vtt 6.9 kB
  • 17 - Project Creating CNN model from scratch/42 - Project Introduction English.vtt 6.9 kB
  • 15 - Creating CNN model in R/37 - Data Preprocessing English.vtt 6.9 kB
  • 2 - Setting Up R Studio and R crash course/3 - Installing R and R studio English.vtt 6.8 kB
  • 18 - Project Data Augmentation for avoiding overfitting/48 - Project in R Data Augmentation English.vtt 6.6 kB
  • 18 - Project Data Augmentation for avoiding overfitting/49 - Project in R Validation Performance English.vtt 6.2 kB
  • 15 - Creating CNN model in R/40 - Model Performance English.vtt 6.0 kB
  • 15 - Creating CNN model in R/38 - Creating Model Architecture English.vtt 5.8 kB
  • 14 - CNN Basics/34 - Channels English.vtt 5.7 kB
  • 14 - CNN Basics/35 - PoolingLayer English.vtt 5.4 kB
  • 2 - Setting Up R Studio and R crash course/7 - Inputting data part 1 Inbuilt datasets of R English.vtt 5.2 kB
  • 17 - Project Creating CNN model from scratch/45 - CNN Project in R Structure and Compile English.vtt 5.1 kB
  • 19 - Transfer Learning Basics/54 - Transfer Learning English.vtt 5.0 kB
  • 14 - CNN Basics/32 - Padding English.vtt 4.5 kB
  • 19 - Transfer Learning Basics/50 - ILSVRC English.vtt 4.1 kB
  • 16 - Analyzing impact of Pooling layer/41 - Comparison Pooling vs Without Pooling in R English.vtt 3.8 kB
  • 2 - Setting Up R Studio and R crash course/4 - This is a milestone English.vtt 3.5 kB
  • 7 - Tensorflow and Keras/19 - Keras and Tensorflow English.vtt 3.5 kB
  • 2 - Setting Up R Studio and R crash course/8 - Inputting data part 2 Manual data entry English.vtt 3.4 kB
  • 1 - Introduction/1 - Introduction English.vtt 3.4 kB
  • 19 - Transfer Learning Basics/53 - GoogLeNet English.vtt 3.0 kB
  • 15 - Creating CNN model in R/39 - Compiling and training English.vtt 2.9 kB
  • 17 - Project Creating CNN model from scratch/46 - Project in R Training English.vtt 2.8 kB
  • 14 - CNN Basics/31 - Stride English.vtt 2.8 kB
  • 7 - Tensorflow and Keras/20 - Installing Keras and Tensorflow English.vtt 2.7 kB
  • 21 - Congratulations & about your certificate/58 - Bonus lecture.html 2.4 kB
  • 17 - Project Creating CNN model from scratch/47 - Project in R Model Performance English.vtt 2.3 kB
  • 15 - Creating CNN model in R/36 - CNN on MNIST Fashion Dataset Model Architecture English.vtt 2.2 kB
  • 19 - Transfer Learning Basics/52 - VGG16NET English.vtt 1.8 kB
  • 19 - Transfer Learning Basics/51 - LeNET English.vtt 1.7 kB
  • 21 - Congratulations & about your certificate/57 - The final milestone English.vtt 1.6 kB
  • 8 - R Dataset for classification problem/22 - More about testtrain split.html 559 Bytes
  • 1 - Introduction/2 - Course Resources.html 333 Bytes
  • 17 - Project Creating CNN model from scratch/43 - Data for the project.html 232 Bytes
  • 0. Websites you may like/[FreeCourseSite.com].url 127 Bytes
  • 0. Websites you may like/[CourseClub.Me].url 122 Bytes
  • 17 - Project Creating CNN model from scratch/43 - Download the project dataset.txt 66 Bytes
  • 0. Websites you may like/[GigaCourse.Com].url 49 Bytes
  • 4 - Neural Networks Stacking cells to create network/1 - Quiz.html 0 Bytes
  • 5 - Important concepts Common Interview questions/2 - Quiz.html 0 Bytes
  • 6 - Standard Model Parameters/3 - Quiz.html 0 Bytes

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