Machine Learning KNIME Hands-On Series (Day 10) - CNN скачать в хорошем качестве

Machine Learning KNIME Hands-On Series (Day 10) - CNN

🎥 Image Classification using Convolutional Neural Networks (CNN) | KNIME Hands-On Tutorial Welcome back to another exciting hands-on session in our AI/ML with KNIME series! In this video, we’ll build an Image Classification model to recognize cats and dogs using a Convolutional Neural Network (CNN) — one of the most powerful deep learning architectures for image processing. 🔹 What You’ll Learn: 1️⃣ How to read and preprocess image data (resize, label, and encode). 2️⃣ How to build a CNN architecture step-by-step using Keras nodes in KNIME. 3️⃣ How to train, test, and evaluate the model for accuracy and performance. 🔹 Workflow Highlights: Image Reading & Labeling (List Files/Folders, Rule Engine) Image Preprocessing (Resizing, Encoding, Filtering) CNN Model Building (Convolution, Max Pooling, Dense, Dropout Layers) Model Training & Evaluation (Keras Network Learner, Scorer Node) By the end, you’ll understand how KNIME integrates AI & Deep Learning to perform image-based predictions — all with a no-code/low-code approach! #ImageClassification #KNIME #DeepLearning #CNN #AI #MachineLearning #NoCodeAI #Keras #CatsVsDogs #NeuralNetworks ‪@InquisitiveMinds-AIPM‬