Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically

Many introductory guides to AI are mathematics books in disguise. This one mostly eschews the math. Instead, author Jeff Prosise helps engineers and software developers build an intuitive understanding of AI to solve business problems. Need to create a system to detect defective parts coming off an assembly line? This practical book teaches you the skills necessary to put AI and machine learning to work at your company.

Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equations--just a fast start for engineers and software developers, complete with hands-on examples.

• Learn what machine learning and deep learning are and what they can accomplish
• Understand how popular learning algorithms work and when to apply them
• Learn the differences between labeled and unlabeled data and between supervised and unsupervised learning
• Build machine learning models in Python with scikit-learn, and neural networks with Keras and TensorFlow
• Train and score regression models and binary- and multiclass-classification models
• Build face-detection and facial recognition models and object-detection models