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tolios g simplifying machine learning pycaret 2022

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Textbook in PDF format A beginner-friendly introduction to Machine Learning (ML) with Python, that is based on the PyCaret and Streamlit libraries. Readers will delve into the fascinating world of Artificial Intelligence (AI), by easily training and deploying their ML models! The field of Machine Learning has grown substantially in the past years due to technological and scientific advancements. Data scientists and machine learning engineers are among the best paid professionals in the modern job market, and demand for associated skills is extremely high. PyCaret is a low-code machine learning Python library that is easy to use, thus making it accessible to beginners. This book provides hands-on tutorials for each of the main PyCaret modules, such as classification, regression, clustering, anomaly detection and natural language processing (NLP). Furthermore, the book will teach you how to develop Machine Learning applications based on the Streamlit library, as well as deploy them on the cloud. Apart from beginners, this book can also be valuable to experts who want to familiarize themselves with the PyCaret library and its features. The following chapters contain hands-on tutorials for the main machine learning modules that are included with PyCaret, such as regression, classification, anomaly detection, clustering and natural language processing. Furthermore, I will also explain how to deploy ML models as web applications, based on the Streamlit library and the associated Streamlit Cloud service. This will let you share your work with others, thus showcasing your skill and expertise. Who this Book is for This book is targeted towards Python developers that want to familiarize themselves with the PyCaret library, as well as machine learning in general. The content is beginner-friendly, so I assume no prior knowledge of machine learning techniques and methods. Experienced data scientists and machine learning engineers can also benefit from reading this book, as it will help them acquaint themselves with the low-code approach of PyCaret, and improve their workflow. This book will focus on practical coding examples, so I will only provide basic explanations of theoretical concepts. Prerequisites You should have some basic knowledge of Python 3, linear algebra, statistics and probability theory. The math included in this book will be minimal, as it isn’t supposed to be a college textbook, but rather a practical guide for developers. Regardless, having a solid understanding of some fundamental mathematical concepts is important. A Brief Introduction to Machine Learning Regression Classification Clustering Anomaly Detection Natural Language Processing Deploying a Machine Learning Model Closing Thoughts

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tolios g simplifying machine learning pycaret 2022