P R.E S E N T S              .

Python: Data Analytics And Visualization

DATE: 2018-07-24  SIZE: 47.91 MB   DISKS: 6x 10MB     PAGES: n/a

PUBLISHER: n/a                               GENRE:

AUTHOR: Phuong Vo.T.H, Martin Czygan, Ashish Kumar

FORMAT: EPUB  PROTECTION: DRM  EDITION: n/a

URL: https://is.gd/mXqPPr

LANGUAGE: English   ISBN: 9781788290098

: Understand, evaluate, and visualize data About This Book - Learn basic     :
: steps of data analysis and how to use Python and its packages - A step-by- :
: step guide to predictive modeling including tips, tricks, and best         :
: practices - Effectively visualize a broad set of analyzed data and generat :
: effective results Who This Book Is For This book is for Python Developers  :
: who are keen to get into data analysis and wish to visualize their analyze :
: data in a more efficient and insightful manner. What You Will Learn - Get  :
: acquainted with NumPy and use arrays and array-oriented computing in data  :
: analysis - Process and analyze data using the time-series capabilities of  :
: Pandas - Understand the statistical and mathematical concepts behind       :
: predictive analytics algorithms - Data visualization with Matplotlib -     :
: Interactive plotting with NumPy, Scipy, and MKL functions - Build financia :
: models using Monte-Carlo simulations - Create directed graphs and multi-   :
: graphs - Advanced visualization with D3 In Detail You will start the cours :
: with an introduction to the principles of data analysis and supported      :
: libraries, along with NumPy basics for statistics and data processing.     :
: Next, you will overview the Pandas package and use its powerful features t :
: solve data-processing problems. Moving on, you will get a brief overview o :
: the Matplotlib API .Next, you will learn to manipulate time and data       :
: structures, and load and store data in a file or database using Python     :
: packages. You will learn how to apply powerful packages in Python to       :
: process raw data into pure and helpful data using examples. You will also  :
: get a brief overview of machine learning algorithms, that is, applying dat :
: analysis results to make decisions or building helpful products such as    :
: recommendations and predictions using Scikit-learn. After this, you will   :
: move on to a data analytics specialization-predictive analytics. Social    :
: media and IOT have resulted in an avalanche of data. You will get started  :
: with predictive analytics using Python. You will see how to create         :
: predictive models from data. You will get balanced information on          :
: statistical and mathematical concepts, and implement them in Python using  :
: libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about :
: the best predictive modeling algorithms such as Linear Regression, Decisio :
: Tree, and Logistic Regression. Finally, you will master best practices in  :
: predictive modeling. After this, you will get all the practical guidance   :
: you need to help you on the journey to effective data visualization.       :
: Starting with a chapter on data frameworks, which explains the             :
: transformation of data into information and eventually knowledge, this pat :
: subsequently cover the complete visualization process using the most       :
: popular Python libraries with working examples This Learning Path combines :
: some of the best that Packt has to offer in one complete, curated package. :
: It includes content from the following Packt products: ? Getting Started   :
: with Python Data Analysis, Phuong Vo.T.H &Martin Czygan ? Learning         :
: Predictive Analytics with Python, Ashish Kumar ? Mastering Python Data     :
: Visualization, Kirthi Raman Style and approach The course acts as a step-  :
: by-step guide to get you familiar with data analysis and the libraries     :
: supported by Python with the help of real-world examples and datasets. It  :
: also helps you gain practical insights into predictive modeling by         :
: implementing predictive-analytics algorithms on public datasets with       :
: Python. The course offers a wealth of practical guidance to help you on    :
: this journey to data visualization                                         :

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