Machine learning and data science are two of the most in-demand skills in today’s job market. If you’re interested in learning more about these topics, then you’re in luck!
TradePub is giving away for free a $156 ebook that explains how machine learning and data science work and how they may be put to use in the real world.
A group of researchers and practitioners prepared this ebook titled “Machine Learning and Data Science: Fundamentals and Applications” with extensive experience in the subject. It starts with the fundamentals of ML and progresses to more complex concepts like deep ML.
The ebook also features case studies showcasing the practical application of data science and machine learning in a variety of settings.
Contents
Get the $156 ebook FREE for a limited time!
To enter the giveaway, go to this TradePub page.
Enter your email address and then click the “Download” button to get started. If you have used TradePub before, please enter your login information.
All new members are asked to fill out a short registration form. After that, look in your inbox for more instructions. The ebook download link has been sent to you through email from TradePub.
The ebook is also available in the TradePub library, which you may access directly. The last day to take advantage of this deal is July 26, 2023.
About Machine Learning and Data Science: Fundamentals and Applications:
Machine learning (ML) and data science (DS) are booming fields that cover a wide range of theoretical and practical aspects. They are recognized as important disciplines shaping research in statistics, computer science, and intelligence science.
These fields also have a transformative impact on science, engineering, the public sector, business, social science, and lifestyle. However, they come with significant challenges that require advanced machine learning and data science methods.
These algorithms include subfields such as artificial intelligence (AI), data analytics (DA), machine learning (ML), pattern recognition (PR), natural language understanding (NLU), and massive data manipulation (DBM).
Scientists in these fields tackle cutting-edge challenges in integrating and analyzing complex resources to enhance decision-making, collaboration, and value creation.
The chapters in this book explore various subjects in ML and DS and offer both conceptual and foundational research.
As part of this scientific reform, the book showcases a diverse array of interdisciplinary applications and innovative advancements that use ML and DS methods to address recent discoveries and outcomes in multiple technical domains.