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Statistics for Data Scientists and Analysts Dipendra Pant, Suresh Kumar Mukhiya

Język publikacji: angielskim
Statistics for Data Scientists and Analysts Dipendra Pant, Suresh Kumar Mukhiya - okladka książki

Statistics for Data Scientists and Analysts Dipendra Pant, Suresh Kumar Mukhiya - okladka książki

Autorzy:
Dipendra Pant, Suresh Kumar Mukhiya
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
376
Dostępne formaty:
     ePub
     Mobi

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Description
Statistics is a powerful tool for data analysis, visualization, and inference. Python is a popular programming language that offers a rich set of libraries and frameworks for statistical computing. Together, they can help you solve real-world problems and make informed decisions based on data. This book teaches you how to use Python to implement statistical concepts and techniques in a practical and effective way. You will also learn how to perform data science and analysis to generate insights, patterns, and trends.

This book introduces the basics of statistics, such as descriptive and inferential statistics, ML, probability distributions, hypothesis testing, and confidence intervals. It also covers advanced topics such as regression analysis, linear algebra, statistical tests, time series, survival, and correlation analysis. You will learn how to identify patterns, interpret data, and make data-driven decisions. The book emphasizes practical learning with examples, exercises, and code snippets using popular Python libraries like NumPy, Pandas, Matplotlib, Seaborn, and SciPy to perform various statistical tasks.

By the end of this book, you will have a solid foundation in statistics and Python programming. You will be able to explore, analyze, and visualize data using Python. You will also be able to perform various statistical tests and interpret the results.

Key Features
Learn how to analyze data using statistics, with a focus on cutting-edge statistical methods, modeling, and visualization.
Explore topics from basic to advanced, including data visualization, statistics, machine learning (ML), and large language models (LLMs).
Includes clear examples, hands-on tutorials, and a real-world project to apply all concepts.

What you will learn
Master data manipulation, cleaning, and visualization techniques using Python.
Apply core statistical methods to analyze real-world datasets.
Build and evaluate statistical models for regression, classification, and clustering.
Interpret and communicate insights derived from statistical analyses effectively.
Explore advanced statistical techniques like time series and survival analysis.

Who this book is for
This book is ideal for data scientists, ML engineers, statisticians, Python practitioners, researchers, and anyone who works with data and statistics.

Table of Contents
1. Foundations of Data Analysis and Python
2. Exploratory Data Analysis
3. Frequency Distribution, Central Tendency, Variability
4. Unravelling Statistical Relationships
5. Estimation and Confidence Intervals
6. Hypothesis and Significance Testing
7. Statistical Machine Learning
8. Unsupervised Machine Learning
9. Linear Algebra, Nonparametric Statistics, and Time Series Analysis
10. Generative AI and Prompt Engineering
11. Real World Statistical Applications

Wybrane bestsellery

O autorze książki

Suresh Kumar Mukhiya is a PhD candidate, currently affiliated to the Western Norway University of Applied Sciences (HVL). He is a big data enthusiast, specializing in Information Systems, Model-Driven Software Engineering, Big Data Analysis, Artificial Intelligence and Frontend development. He has completed a Masters in Information Systems from the Norwegian University of Science and Technology (NTNU, Norway) along with a thesis in processing mining. He also holds a bachelor's degree in computer science and information technology (BSc.CSIT) from Tribhuvan University, Nepal, where he was decorated with the Vice-Chancellor's Award for obtaining the highest score. He is a passionate photographer and a resilient traveler.

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