Discover the fundamentals of deep learning and its practical application using the KNIME Analytics Platform in this informative webinar. Learn about key concepts such as artificial neurons and back-propagation, and gain insights into Convolutional Neural Networks for Computer Vision tasks. Follow along as a simple neural network is built to solve a classification problem using the KNIME Deep Learning - Keras Integration, demonstrating how to define, train, and deploy deep learning models without writing code. Explore the power of neural networks, from basic structures to deep architectures, and understand important considerations like gradient descent, learning rates, and transfer learning. Perfect for those looking to enter the world of deep learning without the coding barrier, this session provides a comprehensive introduction to building and implementing neural networks using a user-friendly, visual approach.
A Friendly Introduction to Codeless Deep Learning with KNIME Analytics Platform
Overview
Syllabus
Introduction
Basic Idea
Example
New Sample
Gradient Descent
Forward Pass
Learning Rate
Important Considerations
Fully Connected Neural Network
When do Neural Network become Deep
Computer Vision
Representation
Encoding
Filters
Filter multiplication
Convolutional layer
Weight
Stride
Pooling
Network Structure
Network Architecture
Transfer Learning
KNIME Hub
Nam Community
Book Recommendation
Webinars
Taught by
Data Science Dojo
