How AI Sees: An Intuitive Guide to Convolutional Neural Networks (CNNs) скачать в хорошем качестве

How AI Sees: An Intuitive Guide to Convolutional Neural Networks (CNNs)

How do Convolutional Neural Networks (CNNs) actually see images? In this video, we break down CNNs visually and intuitively—without heavy math. You’ll learn how CNNs scan images, detect patterns, and make intelligent predictions using layers, filters, and feature maps. We cover the history of CNNs, why traditional neural networks struggled with images, and how convolution, stride, padding, pooling, and dense layers work together to recognize objects like cats, dogs, and cars. This video is ideal for beginners in AI, machine learning, and computer vision who want a clear mental model of how CNNs work. ⏱️ Timestamps 00:00 Introduction – What you’ll learn in this video 01:00 The vision problem CNNs solved 01:35 Evolution to AlexNet, VGG, and ResNet 02:00 The problem with flattening images 03:40 Core idea behind CNNs – Local patterns and translation invariance 04:16 CNN architecture overview 04:39 Convolutional layer explained 05:12 Filters and feature maps visualization 06:13 Model weights and learning process 07:00 Stride explained 07:35 Padding explained 07:54 Activation functions (ReLU) 08:15 Pooling layer explained 09:15 Flattening and dense layers 09:37 Softmax and probability predictions 09:58 Final summary – How CNNs make decisions 🧠 What you'll learn -Why CNNs are essential for image processing -How convolution filters scan images -What stride and padding do -How pooling reduces computation -How CNNs recognize objects step-by-step -How AI converts image features into predictions 🔖 Hashtags #CNN #ConvolutionalNeuralNetworks #DeepLearning #MachineLearning #ArtificialIntelligence #ComputerVision #NeuralNetworks #AIExplained #AIForBeginners #DeepLearningExplained #ComputerVisionBasics #HowAIWorks 👩‍🏫 About the Presenter: Dr. Sindhu Ghanta delivers clear, practical, and mathematically intuitive explanations for complex machine learning algorithms. Her/Our style? No jargon. Just clear, useful explanations that help you learn fast and apply your skills immediately. 🔗 Learn More & Subscribe: Subscribe to @Schovia for weekly AI tutorials, simplified tech, and the latest trends. 🔗 Explore More at Schovia: https://schovia.com/ 🔔 Like, comment, and subscribe for new videos every Tuesday!