Practical Machine Learning with TensorFlow 2.0 and Scikit-Learn: Build effective models in scikit-learn with TensorFlow 2.0

Key benefits

• Embark on your ML journey using the best machine learning practices and the powerful features of TensorFlow 2.0 and scikit-learn
• Learn to work with unstructured data, images, and noisy text input, and implement the latest Natural Language Processing models and methods
• Explore supervised and unsupervised algorithms and put them into practice using mini implementation projects as a basis for real-world applications

Description

Who is this book for?

What you will learn

• Fundamentals of machine learning (and introducing the benefits of scikit-learn)
• Practical implementation with comprehensive examples of canonical machine learning, and supervised and unsupervised machine learning in scikit-learn
• How to identify a problem, select the right model, and optimize it to get the best desired outcome: insights into data
• TensorFlow 2.0 for deep learning with neural networks
• Deep learning and image-classification examples, and time series predictive model examples
• Reinforcement learning, and how to implement various types with examples
• Effectively use scikit-learn and TensorFlow in your production system, including framing a task in each task example