Numpy Cookbook Second Edition
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Numpy Cookbook Second Edition
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Author : Ivan Idris
language : en
Publisher: Packt Publishing
Release Date : 2015-04-30
Numpy Cookbook Second Edition written by Ivan Idris and has been published by Packt Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-30 with Computers categories.
The Official Raspberry Pi Projects Book Volume 2
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Author : The Makers of The MagPi magazine
language : en
Publisher: Raspberry Pi Press
Release Date : 2016-11-01
The Official Raspberry Pi Projects Book Volume 2 written by The Makers of The MagPi magazine and has been published by Raspberry Pi Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-01 with Computers categories.
The Official Raspberry Pi projects book returns with inspirational projects, detailed step-by-step guides, and product reviews based around the phenomenon that is the Raspberry Pi. See why educators and makers adore the credit card-sized computer that can be used to make robots, retro games consoles, and even art. In this volume of The Official Raspberry Pi Projects Book, you'll: Get involved with the amazing and very active Raspberry Pi community Be inspired by incredible projects made by other people Learn how to make with your Raspberry Pi with our tutorials Find out about the top kits and accessories for your Pi projects And much, much more! If this is your first time using a Raspberry Pi, you'll also find some very helpful guides to get you started with your Raspberry Pi journey. With millions of Raspberry Pi boards out in the wild, that's millions more people getting into digital making and turning their dreams into a Pi-powered reality. Being so spoilt for choice though means that we've managed to compile an incredible list of projects, guides, and reviews for you. This book was written using an earlier version of Raspberry Pi OS. Please use Raspberry Pi OS (Legacy) for full compatibility. See magpi.cc/legacy for more information.
Python Data Analysis Cookbook
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Author : Ivan Idris
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-07-22
Python Data Analysis Cookbook written by Ivan Idris and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-22 with Computers categories.
Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps About This Book Analyze Big Data sets, create attractive visualizations, and manipulate and process various data types Packed with rich recipes to help you learn and explore amazing algorithms for statistics and machine learning Authored by Ivan Idris, expert in python programming and proud author of eight highly reviewed books Who This Book Is For This book teaches Python data analysis at an intermediate level with the goal of transforming you from journeyman to master. Basic Python and data analysis skills and affinity are assumed. What You Will Learn Set up reproducible data analysis Clean and transform data Apply advanced statistical analysis Create attractive data visualizations Web scrape and work with databases, Hadoop, and Spark Analyze images and time series data Mine text and analyze social networks Use machine learning and evaluate the results Take advantage of parallelism and concurrency In Detail Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning. Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You'll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining. In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code. By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios. Style and Approach The book is written in “cookbook” style striving for high realism in data analysis. Through the recipe-based format, you can read each recipe separately as required and immediately apply the knowledge gained.
Python Data Analysis
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Author : Avinash Navlani
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-05
Python Data Analysis written by Avinash Navlani and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-05 with Computers categories.
Understand data analysis pipelines using machine learning algorithms and techniques with this practical guide Key FeaturesPrepare and clean your data to use it for exploratory analysis, data manipulation, and data wranglingDiscover supervised, unsupervised, probabilistic, and Bayesian machine learning methodsGet to grips with graph processing and sentiment analysisBook Description Data analysis enables you to generate value from small and big data by discovering new patterns and trends, and Python is one of the most popular tools for analyzing a wide variety of data. With this book, you'll get up and running using Python for data analysis by exploring the different phases and methodologies used in data analysis and learning how to use modern libraries from the Python ecosystem to create efficient data pipelines. Starting with the essential statistical and data analysis fundamentals using Python, you'll perform complex data analysis and modeling, data manipulation, data cleaning, and data visualization using easy-to-follow examples. You'll then understand how to conduct time series analysis and signal processing using ARMA models. As you advance, you'll get to grips with smart processing and data analytics using machine learning algorithms such as regression, classification, Principal Component Analysis (PCA), and clustering. In the concluding chapters, you'll work on real-world examples to analyze textual and image data using natural language processing (NLP) and image analytics techniques, respectively. Finally, the book will demonstrate parallel computing using Dask. By the end of this data analysis book, you'll be equipped with the skills you need to prepare data for analysis and create meaningful data visualizations for forecasting values from data. What you will learnExplore data science and its various process modelsPerform data manipulation using NumPy and pandas for aggregating, cleaning, and handling missing valuesCreate interactive visualizations using Matplotlib, Seaborn, and BokehRetrieve, process, and store data in a wide range of formatsUnderstand data preprocessing and feature engineering using pandas and scikit-learnPerform time series analysis and signal processing using sunspot cycle dataAnalyze textual data and image data to perform advanced analysisGet up to speed with parallel computing using DaskWho this book is for This book is for data analysts, business analysts, statisticians, and data scientists looking to learn how to use Python for data analysis. Students and academic faculties will also find this book useful for learning and teaching Python data analysis using a hands-on approach. A basic understanding of math and working knowledge of the Python programming language will help you get started with this book.
Python Data Analysis
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Author : Armando Fandango
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-03-27
Python Data Analysis written by Armando Fandango and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-27 with Computers categories.
Learn how to apply powerful data analysis techniques with popular open source Python modules About This Book Find, manipulate, and analyze your data using the Python 3.5 libraries Perform advanced, high-performance linear algebra and mathematical calculations with clean and efficient Python code An easy-to-follow guide with realistic examples that are frequently used in real-world data analysis projects. Who This Book Is For This book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients you need to become an expert data analyst. What You Will Learn Install open source Python modules such NumPy, SciPy, Pandas, stasmodels, scikit-learn,theano, keras, and tensorflow on various platforms Prepare and clean your data, and use it for exploratory analysis Manipulate your data with Pandas Retrieve and store your data from RDBMS, NoSQL, and distributed filesystems such as HDFS and HDF5 Visualize your data with open source libraries such as matplotlib, bokeh, and plotly Learn about various machine learning methods such as supervised, unsupervised, probabilistic, and Bayesian Understand signal processing and time series data analysis Get to grips with graph processing and social network analysis In Detail Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries. Style and approach The book takes a very comprehensive approach to enhance your understanding of data analysis. Sufficient real-world examples and use cases are included in the book to help you grasp the concepts quickly and apply them easily in your day-to-day work. Packed with clear, easy to follow examples, this book will turn you into an ace data analyst in no time.
Time Series Analysis With Python Cookbook
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Author : Tarek A. Atwan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2026-01-16
Time Series Analysis With Python Cookbook written by Tarek A. Atwan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2026-01-16 with Computers categories.
Perform time series analysis and forecasting confidently with this Python code bank and reference manual. Access exclusive GitHub bonus chapters and hands-on recipes covering Python setup, probabilistic deep learning forecasts, frequency-domain analysis, large-scale data handling, databases, InfluxDB, and advanced visualizations. Purchase of the print or Kindle book includes a free PDF eBook Key Features Explore up-to-date forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms Learn different techniques for evaluating, diagnosing, and optimizing your models Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book DescriptionTo use time series data to your advantage, you need to master data preparation, analysis, and forecasting. This fully refreshed second edition helps you unlock insights from time series data with new chapters on probabilistic models, signal processing techniques, and new content on transformers. You’ll work with the latest releases of popular libraries like Pandas, Polars, Sktime, stats models, stats forecast, Darts, and Prophet through up-to-date examples. You'll hit the ground running by ingesting time series data from various sources and formats and learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods. Through detailed instructions, you'll explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR, and learn practical techniques for handling non-stationary data using power transforms, ACF and PACF plots, and decomposing time series data with seasonal patterns. The recipes then level up to cover more advanced topics such as building ML and DL models using TensorFlow and PyTorch and applying probabilistic modeling techniques. In this part, you’ll also be able to evaluate, compare, and optimize models, finishing with a strong command of wrangling data with Python.What you will learn Understand what makes time series data different from other data Apply imputation and interpolation strategies to handle missing data Implement an array of models for univariate and multivariate time series Plot interactive time series visualizations using hvPlot Explore state-space models and the unobserved components model (UCM) Detect anomalies using statistical and machine learning methods Forecast complex time series with multiple seasonal patterns Use conformal prediction for constructing prediction intervals for time series Who this book is for This book is for data analysts, business analysts, data scientists, data engineers, and Python developers who want to learn time series analysis and forecasting techniques step by step through practical Python recipes. To get the most out of this book, you’ll need fundamental Python programming knowledge. Prior experience working with time series data to solve business problems will help you to better utilize and apply the recipes more quickly.
Software Engineering And Management Theory And Applications
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Author : Roger Lee
language : en
Publisher: Springer Nature
Release Date : 2025-04-26
Software Engineering And Management Theory And Applications written by Roger Lee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-26 with Computers categories.
This book reports state-of-the-art results in Software Engineering Research, Management & Applications in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world. This book published original papers on both theory and practice that address foundations, state-of-the-art problems and solutions, and crucial challenges.
Numpy Beginner S Guide
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Author : Ivan Idris
language : en
Publisher:
Release Date : 2013
Numpy Beginner S Guide written by Ivan Idris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Programming languages (Electronic computers) categories.
Numpy Beginner S Guide
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Author : Ivan Idris
language : en
Publisher:
Release Date : 2013
Numpy Beginner S Guide written by Ivan Idris and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Electronic books categories.
The book is written in beginner's guide style with each aspect of NumPy demonstrated with real world examples and required screenshots.If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.
Fluent Python
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Author : Luciano Ramalho
language : en
Publisher: O'Reilly Media
Release Date : 2015
Fluent Python written by Luciano Ramalho and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.
Explains how to write idiomatic, effective Python code by leveraging its best features. Python's simplicity quickly lets you become productive with it, but this often means you aren't using everything the language has to offer. By taking you through Python's key language features and libraries, this practical book shows you how to make your code shorter, faster, and more readable all at the same time. --From publisher description.