More Information
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
About

Machine 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.

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
Page Count 286
Course Length 8 hours 34 minutes
ISBN 9781839219061
Date Of Publication 22 Jul 2020

Authors

Hyatt Saleh

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored the book Machine Learning Fundamentals, by Packt Publishing.