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Sparse Estimation with Math and R

) - Statistical Learning with Math and Python (https://www.springer.com/gp/book/9789811578762) - Sparse Estimation with Math and Python;

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Sparse Estimation with Math and Python

learning by the same Author. Other titles are: Statistical Learning with Math and R (https://www.springer.com/gp/book/9789811575679;

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Statistical Learning with Math and Python

experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs;

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Training Systems Using Python Statistical Modeling

, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive;

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Math For Deep Learning

With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll work through;

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Linear Models with Python

Selection, Shrinkage, Experiments with Blocks and Missing Data. Includes an Appendix on Python for beginners.;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Building Machine Learning Systems With Python

-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML;

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Math Adventures With Python

Learn maths by getting creative with code! In Math Adventures with Python, teacher and programmer Peter Farrell shows you how to explore;

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Learning Pandas

and incremental examples to facilitate learning Who This Book Is ForIf you are a Python programmer who wants to get started with performing;

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Essential Statistics for Non-STEM Data Analysts

results produced by data science pipelines. This book is a detailed guide covering the math and various statistical methods required for;

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Python for Probability, Statistics, and Machine Learning

, and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but also;

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Statistical Application Development with R and Python -

preliminary concepts right away using R and Python. * Understand data modeling and visualization to perform efficient statistical analysis with this;

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Numerical Python

, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and;

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Data Science from Scratch: First Principles with Python

with some programming skills. The book covers: The important parts of Python to know The important parts of Math / Probability / Statistics to;

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Python Machine Learning

elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.;

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Machine Learning with Python

success. This guide is meant to help you with understanding the fundamentals of Machine Learning with Python, as well as making predictions and;

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Mastering Python Data Analysis

in data * Review classical statistical inference using Python, Pandas, and SciPy * Detect similarities and differences in data with clustering;

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Machine Learning with Python for Everyone

The Complete Beginner's Guide to Understanding and Building Machine Learning Systems with Python Machine Learning with Python for;

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Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a;

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Natural Language Processing and Computational Linguistics

explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to;

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An Introduction to Statistics with Python

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical;

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Machine Learning for Finance

book is ideal for readers who understand math and Python, and want to adopt machine learning in financial applications. The book assumes;

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Introduction to Machine Learning with Python

the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and;

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Python Data Science Handbook

with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues;

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Practical Data Science with Python

utilize data science tools in Python, such as specialized machine learning algorithms and statistical modeling Build a strong data science;

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