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-AI

Видео Machine Learning KNIME Hands-On Series (Day 10) - CNN канала InquisitiveMinds - AI