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Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python Curtis Miller

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Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python Curtis Miller - okladka książki

Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python Curtis Miller - okladka książki

Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python Curtis Miller - audiobook MP3

Training Systems using Python Statistical Modeling. Explore popular techniques for modeling your data in Python Curtis Miller - audiobook CD

Autor:
Curtis Miller
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
290
Dostępne formaty:
     PDF
     ePub
     Mobi
Python's ease-of-use and multi-purpose nature has made it one of the most popular tools for data scientists and machine learning developers. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book is designed to guide you through using these libraries to implement effective statistical models for predictive analytics.
You’ll start by delving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will focus on supervised learning, which will help you explore the principles of machine learning and train different machine learning models from scratch. Next, you will work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. The book will also cover algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. In later chapters, you will learn how neural networks can be trained and deployed for more accurate predictions, and understand which Python libraries can be used to implement them.
By the end of this book, you will have the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics.

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O autorze książki

Curtis Miller is a doctoral candidate at the University of Utah studying mathematical statistics. He writes software for both research and personal interest, including the R package (CPAT) available on the Comprehensive R Archive Network (CRAN). Among Curtis Miller's publications are academic papers along with books and video courses all published by Packt Publishing. Curtis Miller's video courses include Unpacking NumPy and Pandas, Data Acquisition and Manipulation with Python, Training Your Systems with Python Statistical Modelling, and Applications of Statistical Learning with Python. His books include Hands-On Data Analysis with NumPy and Pandas.

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