Machine Learning for Developers: Uplift your regular applications with the power of statistics, analytics, and machine learning
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Author Description
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THE THESIS
This book investigates how developers can integrate machine learning techniques into their existing applications to enhance functionality and performance. It aims to bridge the gap between theoretical machine learning concepts and practical software development, providing actionable insights for developers. The content focuses on leveraging statistics and analytics to build more intelligent and responsive applications, moving beyond traditional programming paradigms.
THE SCOPE MAP
- Introduction to Machine Learning concepts for developers
- Statistical foundations for data analysis
- Analytical techniques for understanding application performance
- Practical methods for integrating ML models into applications
- Case studies demonstrating uplifted application capabilities
- Overview of relevant algorithms and their implementation
- Best practices for deploying ML-enhanced applications
THE AUTHORITY PERSPECTIVE
The book is positioned as a practical guide for developers seeking to incorporate machine learning into their work. Its focus on statistics and analytics suggests a data-driven approach to enhancing application intelligence. The premise indicates a target audience of software engineers looking to expand their skill set with modern AI techniques.
Page Count:
270
Publication Date:
2017-01-01
ISBN-10:
1786469871
ISBN-13:
9781786469878
Non-Fiction
Science & Technology
Data Science
Statistics
Analytics
Machine Learning
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