Download Introduction to Deep Learning Using R A StepbyStep Guide Ebook PDF

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Previews: From the Back Cover Understand deep learning, the nuances of its different models, and where these models can be applied.The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a theoretical and practical understanding of the models that perform these tasks by building upon the fundamentals of data science through machine learning and deep learning. This step-by-step guide will help you understand the disciplines so that you can apply the methodology in a variety of contexts. All examples are taught in the R statistical language, allowing students and professionals to implement these techniques using open source tools.What You Will Learn:• Understand the intuition and mathematics that power deep learning models• Utilize various algorithms using the R programming language and its packages• Use best practices for experimental design and variable selection• Practice the methodology to approach and effectively solve problems as a data scientist• Evaluate the effectiveness of algorithmic solutions and enhance their predictive power Read more About the Author Taweh Beysolow II is a Machine Learning Scientist currently based in the United States with a passion for research and applying machine learning methods to solve problems. He has a Bachelor of Science degree in Economics from St. Johns University and a Master of Science in Applied Statistics from Fordham University. Currently, he is extremely passionate about all matters related to machine learning, data science, quantitative finance, and economics. Read more

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