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Ships within 48 hours · Estimated delivery Jul 11 - Jul 16
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Description
Developing AI ApplicationsDescription Its time to get practical about AI. Move past playing around with chat bots and plugging your data into others applications learn how to create your own! Walk through key AI methods like decision trees, convolution layers, cluster analysis, and more. Get your hands dirty with simple no code exercises and then apply that knowledge to more complex (but still beginner friendly!) examples. With information on installing KNIME and using tools
Description Its time to get practical about AI. Move past playing around with chat bots and plugging your data into others applications learn how to create your own! Walk through key AI methods like decision trees, convolution layers, cluster analysis, and more. Get your hands dirty with simple no-code exercises and then apply that knowledge to more complex (but still beginner-friendly!) examples. With information on installing KNIME and using tools like AutoKeras, ChatGPT, and DALL-E, this guide will let you do more with AI!
Learn to program your own AI applicationseven if youve never coded before!
Get started without code using the KNIME platform and then expand your skills programming with basic Python
Work with neural networks, transfer learning, anomaly detection, reinforcement learning, and more
AI Algorithms Understand the theory and structure behind the most useful AI models and methods and how they can be used to solve problems. Learn about artificial neural networks, anomaly detections, cluster analysis, text and image classification, reinforcement learning, and other algorithms.Tools and Platforms Install and use AI platforms like KNIME and Anaconda. See how tools like ChatGPT and libraries like XGBoost can enhance your AI applications.Practical Exercises Get step--step instructions for creating AI applications, whether youre implementing them with no code on the KNIME platform or programming them using basic Python.
Python
KNIME
ChatGPT
DALL-E
Artificial neural networks (ANN)
Decision trees
Convolution layers
Transfer learning
Anomaly detection
Text and image classification
Cluster analysis
Reinforcement learning
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