Практика про свертки | Почему Dense сетей не достаточно? | НЕЙРОННЫЕ СЕТИ 10.2 часть 1

✔ Practical assignment here ➤ https://boosty.to/machine_learrrning/... ⚠️ All links to my platforms and courses are here: https://taplink.cc/machine_learrrning You can support the channel by subscribing to 🎉 https://boosty.to/machine_learrrning 🎉 https://vk.com/machine_learrrning 🎉 You can also donate coins to https://www.donationalerts.com/r/mach... TG channel https://t.me/machine_learrrning VK group https://vk.com/machine_learrrning Courses on the Stepik platform: 1. Python libraries for Data Science https://stepik.org/a/129105 2. Introduction to Neural Networks (Keras/Tensorflow) https://stepik.org/a/127274 ❓ Questions we'll answer in this video: Why do we need other layers if we already know Fully Connected/Linear/Dense? What is a convolution? 💾 Convolution Theory    • Сверточный слой и слой Pooling в keras | C...   💾 Neural Network Playlist    • Введение в нейронные сети на Keras и Tenso...   🤖 Notebook from the video https://colab.research.google.com/dri... 0:00 Introduction 0:20 Lesson Plan 1:12 Support https://taplink.cc/machine_learrrning 1:30 Installing the Required Library Versions 1:39 Preparing a Dataset for Multiclass Classification 4:21 LabelEncoder for Classes 5:17 Sequence Tensorflow 5:50 _len_ in Sequence 6:06 _getitem_ in Sequence 7:20 Example of a class for generating objects in TensorFlow 8:22 Creating a fully connected network for images 10:15 A reminder about the difference between SparseCategoricalCrossentropy and CategoricalCrossentropy 11:18 Training a fully connected network on images 12:13 Convolution: A Simple Example 12:53 The Mathematics of Convolution 13:41 A Function for Applying Convolution to an Image 15:36 Applying Convolution to a Grayscale Image 16:20 Averaging Filter / Averaging Convolution 18:15 Convolution for Sharpening / Filter for Sharpening 18:38 Sobel Filter / Filter for Finding Edges in an Image 20:00 Replacing Weights in a Conv2D Layer in Keras 21:20 What Should the Weights Be for a Conv2D Layer in Keras, and What Dimension 22:40 Averaging Filter in Conv2D 23:25 Applying convolution to a color image 24:03 Convolution in a simple color example 25:30 Applying convolution per channel 27:54 Replacing weights in a Conv2D layer with multiple channels in Keras 30:43 How non-square convolutions work 33:48 Example of a non-square convolution where the dimension is wider 34:28 Stay tuned for the next video 34:59 ♡