| 1. Basic Terminologies.mp4 | 40.4 MB | ||
| 1. Basic Terminologies.srt | 9.5 KB | ||
| 1. Building Neural Network for Regression Problem.mp4 | 155.9 MB | ||
| 1. Building Neural Network for Regression Problem.srt | 21.9 KB | ||
| 1. CNN Introduction.mp4 | 51.2 MB | ||
| 1. CNN Introduction.srt | 7.8 KB | ||
| 1. CNN model in Python - Preprocessing.mp4 | 40.6 MB | ||
| 1. CNN model in Python - Preprocessing.srt | 5.5 KB | ||
| 1. Comparison - Pooling vs Without Pooling in Python.mp4 | 58 MB | ||
| 1. Comparison - Pooling vs Without Pooling in Python.srt | 5.3 KB | ||
| 1. Dataset for classification.mp4 | 56.2 MB | ||
| 1. Dataset for classification.srt | 7.2 KB | ||
| 1. Different ways to create ANN using Keras.mp4 | 10.8 MB | ||
| 1. Different ways to create ANN using Keras.srt | 1.9 KB | ||
| 1. Hyperparameter Tuning.mp4 | 60.7 MB | ||
| 1. Hyperparameter Tuning.srt | 9.4 KB | ||
| 1. Hyperparameters.mp4 | 45.4 MB | ||
| 1. Hyperparameters.srt | 8.9 KB | ||
| 1. ILSVRC.mp4 | 20.9 MB | ||
| 1. ILSVRC.srt | 4.4 KB | ||
| 1. Installing Python and Anaconda.mp4 | 16.3 MB | ||
| 1. Installing Python and Anaconda.srt | 2.6 KB | ||
| 1. Introduction.mp4 | 22.6 MB | ||
| 1. Introduction.srt | 3.6 KB | ||
| 1. Keras and Tensorflow.mp4 | 14.9 MB | ||
| 1. Keras and Tensorflow.srt | 3.6 KB | ||
| 1. Perceptron.mp4 | 44.8 MB | ||
| 1. Perceptron.srt | 9.7 KB | ||
| 1. Project - Data Augmentation Preprocessing.mp4 | 41.4 MB | ||
| 1. Project - Data Augmentation Preprocessing.srt | 6.7 KB | ||
| 1. Project - Introduction.mp4 | 49.4 MB | ||
| 1. Project - Introduction.srt | 7.1 KB | ||
| 1. Project - Transfer Learning - VGG16.mp4 | 129.1 MB | ||
| 1. Project - Transfer Learning - VGG16.srt | 18.9 KB | ||
| 1. Saving - Restoring Models and Using Callbacks.mp4 | 151.6 MB | ||
| 1. Saving - Restoring Models and Using Callbacks.srt | 18.8 KB | ||
| 1. Some Important Concepts.mp4 | 62.2 MB | ||
| 1. Some Important Concepts.srt | 13.1 KB | ||
| 1. The final milestone!.mp4 | 11.9 MB | ||
| 1. The final milestone!.srt | 1.7 KB | ||
| 1. Using Functional API for complex architectures.mp4 | 92.2 MB | ||
| 1. Using Functional API for complex architectures.srt | 11.9 KB | ||
| 10. Working with Seaborn Library of Python.mp4 | 40.4 MB | ||
| 10. Working with Seaborn Library of Python.srt | 7.5 KB | ||
| 2. Activation Functions.mp4 | 34.6 MB | ||
| 2. Activation Functions.srt | 7.9 KB | ||
| 2. Building the Neural Network using Keras.mp4 | 79.1 MB | ||
| 2. Building the Neural Network using Keras.srt | 12 KB | ||
| 2. CNN model in Python - structure and Compile.mp4 | 43.3 MB | ||
| 2. CNN model in Python - structure and Compile.srt | 6.7 KB | ||
| 2. Congratulations & About your certificate.html | 1.6 KB | ||
| 2. Course Resources.html | 307.2 B | ||
| 2. Data for the project.html | 204.8 B | ||
| 2. Gradient Descent.mp4 | 60.3 MB | ||
| 2. Gradient Descent.srt | 11.9 KB | ||
| 2. Installing Tensorflow and Keras.mp4 | 20.1 MB | ||
| 2. Installing Tensorflow and Keras.srt | 3.8 KB | ||
| 2. LeNET.mp4 | 7 MB | ||
| 2. LeNET.srt | 1.6 KB | ||
| 2. Normalization and Test-Train split.mp4 | 44.2 MB | ||
| 2. Normalization and Test-Train split.srt | 5.7 KB | ||
| 2. Project - Data Augmentation Training and Results.mp4 | 53.1 MB | ||
| 2. Project - Data Augmentation Training and Results.srt | 6.4 KB | ||
| 2. Quiz.html | 204.8 B | ||
| 2. Stride.mp4 | 16.6 MB | ||
| 2. Stride.srt | 2.7 KB | ||
| 2. This is a milestone!.mp4 | 20.7 MB | ||
| 2. This is a milestone!.srt | 3.8 KB | ||
| 2.1 Dataset.html | 102.4 B | ||
| 3. Back Propagation.mp4 | 122.2 MB | ||
| 3. Back Propagation.srt | 22.8 KB | ||
| 3. CNN model in Python - Training and results.mp4 | 55.1 MB | ||
| 3. CNN model in Python - Training and results.srt | 6.1 KB | ||
| 3. Compiling and Training the Neural Network model.mp4 | 81.7 MB | ||
| 3. Compiling and Training the Neural Network model.srt | 9.6 KB | ||
| 3. More about test-train split.html | 512 B | ||
| 3. Opening Jupyter Notebook.mp4 | 65.2 MB | ||
| 3. Opening Jupyter Notebook.srt | 9.1 KB | ||
| 3. Padding.mp4 | 31.6 MB | ||
| 3. Padding.srt | 4.6 KB | ||
| 3. Project - Data Preprocessing in Python.mp4 | 71.9 MB | ||
| 3. Project - Data Preprocessing in Python.srt | 8.6 KB | ||
| 3. Python - Creating Perceptron model.mp4 | 86.6 MB | ||
| 3. Python - Creating Perceptron model.srt | 14.5 KB | ||
| 3. VGG16NET.mp4 | 10.4 MB | ||
| 3. VGG16NET.srt | 1.9 KB | ||
| 4. Evaluating performance and Predicting using Keras.mp4 | 70 MB | ||
| 4. Evaluating performance and Predicting using Keras.srt | 9 KB | ||
| 4. Filters and Feature maps.mp4 | 52.7 MB | ||
| 4. Filters and Feature maps.srt | 6.5 KB | ||
| 4. GoogLeNet.mp4 | 21.4 MB | ||
| 4. GoogLeNet.srt | 3 KB | ||
| 4. Introduction to Jupyter.mp4 | 40.9 MB | ||
| 4. Introduction to Jupyter.srt | 12.3 KB | ||
| 4. Project - Training CNN model in Python.mp4 | 66 MB | ||
| 4. Project - Training CNN model in Python.srt | 8.7 KB | ||
| 4. Quiz.html | 204.8 B | ||
| 5. Arithmetic operators in Python Python Basics.mp4 | 12.7 MB | ||
| 5. Arithmetic operators in Python Python Basics.srt | 4 KB | ||
| 5. Channels.mp4 | 67.7 MB | ||
| 5. Channels.srt | 5.9 KB | ||
| 5. Project in Python - model results.mp4 | 21 MB | ||
| 5. Project in Python - model results.srt | 2.7 KB | ||
| 5. Transfer Learning.mp4 | 30 MB | ||
| 5. Transfer Learning.srt | 5.3 KB | ||
| 6. PoolingLayer.mp4 | 46.9 MB | ||
| 6. PoolingLayer.srt | 5.1 KB | ||
| 6. Strings in Python Python Basics.mp4 | 64.4 MB | ||
| 6. Strings in Python Python Basics.srt | 16.4 KB | ||
| 7. Lists, Tuples and Directories Python Basics.mp4 | 60.3 MB | ||
| 7. Lists, Tuples and Directories Python Basics.srt | 17 KB | ||
| 7. Quiz.html | 204.8 B | ||
| 8. Working with Numpy Library of Python.mp4 | 43.9 MB | ||
| 8. Working with Numpy Library of Python.srt | 10.5 KB | ||
| 9. Working with Pandas Library of Python.mp4 | 46.9 MB | ||
| 9. Working with Pandas Library of Python.srt | 8.2 KB | ||
| [CourseClub.ME].url | 102.4 B | ||
| [FCS Forum].url | 102.4 B | ||
| [FreeCourseSite.com].url | 102.4 B | ||
| [GigaCourse.Com].url | 0 B | ||
| ▲ 121 total files | |||
Udemy - Convolutional Neural Networks in Python: CNN Computer Vision [FCS]
Python for Computer Vision & Image Recognition - Deep Learning Convolutional Neural Network (CNN) - Keras & TensorFlow 2
Created by Start-Tech Academy
Last updated 11/2021
English
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Our Forum for Discussion: https://forum.freecoursesite.com
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