Machine Learning Logistics
Real World Reinforcement Learning Real-World RL projects enable the next generation of machine learning using interactive reinforcement-based approaches to solve real-world problems. The heart of the Real-World RL projects and applications is a platform striving to enable people and organizations to continuously learn and adapt. Goal : To provide complex. Approach : Complex. The pilot specifically targeted the Surface. Approach : The Real-World RL platform was used to personalize different calls-to-action in three different webpages on the Surface.
Get this from a library! Real-world machine learning. [Henrik Brink; Joseph W Richards; Mark Fetherolf].
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1. What is machine learning?
With an OverDrive account, you can save your favorite libraries for at-a-glance information about availability. Find out more about OverDrive accounts. Learn to solve challenging data science problems by building powerful machine learning models using Python About This Book Understand which algorithms to use in a given context with the help of this exciting recipe-based guide This practical tutorial tackles real-world computing problems through a rigorous and effective approach Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected.