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OverviewTake a comprehensive and step-by-step approach to understanding machine learning Key Features Discover how to apply the scikit-learn uniform API in all types of machine learning models Understand the difference between supervised and unsupervised learning models Reinforce your understanding of machine learning concepts by working on real-world examples Book DescriptionMachine learning algorithms are an integral part of almost all modern applications. To make the learning process faster and more accurate, you need a tool flexible and powerful enough to help you build machine learning algorithms quickly and easily. With The Machine Learning Workshop, you'll master the scikit-learn library and become proficient in developing clever machine learning algorithms. The Machine Learning Workshop begins by demonstrating how unsupervised and supervised learning algorithms work by analyzing a real-world dataset of wholesale customers. Once you've got to grips with the basics, you'll develop an artificial neural network using scikit-learn and then improve its performance by fine-tuning hyperparameters. Towards the end of the workshop, you'll study the dataset of a bank's marketing activities and build machine learning models that can list clients who are likely to subscribe to a term deposit. You'll also learn how to compare these models and select the optimal one. By the end of The Machine Learning Workshop, you'll not only have learned the difference between supervised and unsupervised models and their applications in the real world, but you'll also have developed the skills required to get started with programming your very own machine learning algorithms. What you will learn Understand how to select an algorithm that best fits your dataset and desired outcome Explore popular real-world algorithms such as K-means, Mean-Shift, and DBSCAN Discover different approaches to solve machine learning classification problems Develop neural network structures using the scikit-learn package Use the NN algorithm to create models for predicting future outcomes Perform error analysis to improve your model's performance Who this book is forThe Machine Learning Workshop is perfect for machine learning beginners. You will need Python programming experience, though no prior knowledge of scikit-learn and machine learning is necessary. Full Product DetailsAuthor: Hyatt SalehPublisher: Packt Publishing Limited Imprint: Packt Publishing Limited Edition: 2nd Revised edition ISBN: 9781839219061ISBN 10: 1839219068 Pages: 286 Publication Date: 22 July 2020 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Available To Order We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsTable of Contents Introduction to Scikit-Learn Unsupervised Learning - Real-Life Applications Supervised Learning - Key Steps Supervised Learning Algorithms: Predicting Annual Income Artificial Neural Networks: Predicting Annual Income Building Your Own ProgramReviewsAuthor InformationHyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating as a business administrator. She then began her journey as a self-taught machine learning freelancer, working for several companies globally, and even founded an artificial intelligence company that aims to optimize everyday processes. Hyatt has also authored the book Machine Learning Fundamentals by Packt Publishing. Tab Content 6Author Website:Countries AvailableAll regions |
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