Machine Learning Essentials: A Practical Guide to Building Accurate and Reliable Models
Author | : Devansh Dhiman |
Publisher | : Devansh Dhiman |
Total Pages | : 9 |
Release | : 2023-05-01 |
ISBN-10 | : |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Machine Learning Essentials: A Practical Guide to Building Accurate and Reliable Models written by Devansh Dhiman and published by Devansh Dhiman. This book was released on 2023-05-01 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning is a powerful tool for making accurate predictions and improving decision-making based on data-driven insights. However, building accurate and reliable machine learning models requires a thorough understanding of the machine learning workflow, from data preprocessing and exploration to model training and deployment. In this ebook, we provide a practical guide to machine learning essentials, covering everything from the basics of supervised and unsupervised learning to deep learning and model deployment. We explore common machine learning algorithms, including decision trees, support vector machines, and neural networks, and provide examples of how they can be used in real-world applications. We also delve into data preprocessing and exploration, discussing techniques for cleaning, transforming, and scaling data to make it suitable for analysis, and exploring ways to gain insights into the properties and relationships of the data. We discuss best practices for model training and evaluation, and explore strategies for deploying and maintaining machine learning models in a production environment. Whether you're an experienced data scientist or just starting out, this ebook provides a comprehensive guide to building accurate and reliable machine learning models that can transform your business and improve decision-making based on data-driven insights.