Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Numerical Computing with Python: Harness the power of Python to analyze and find hidden patterns in the data

Author
Pratap Dangeti, Allen Yu, Claire Chung, Aldrin Yim, Theodore Petrou
Publisher
Packt Publishing
Language
English
Year
2018
ISBN
9781789953633
File Type
epub
File Size
33.0 MiB

**Understand, explore, and effectively present data using the powerful data visualization techniques of Python**Key Features* Use the power of Pandas and Matplotlib to easily solve data mining issues* Understand the basics of statistics to build powerful predictive data models* Grasp data mining concepts with helpful use-cases and examplesBook DescriptionData mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining.You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models.By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional.This Learning Path includes content from the following Packt products:* Statistics for Machine Learning by Pratap Dangeti* Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim* Pandas Cookbook by Theodore PetrouWhat you will learn* Understand the statistical fundamentals to build data models* Split data into independent groups* Apply aggregations and transformations to each group* Create impressive data visualizations* Prepare your data and design models* Clean up data to ease data analysis and visualization* Create insightful visualizations with Matplotlib and Seaborn* Customize the model to suit your own predictive goalsWho this book is forIf you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.Table of Contents1. Journey from Statistics to Machine Learning2. Tree-Based Machine Learning Models3. K-Nearest Neighbors and Naive Bayes4. Unsupervised Learning5. Reinforcement Learning6. Hello Plotting World!7. Visualizing Online Data8. Visualizing Multivariate Data9. Adding Interactivity and Animating Plots10. Selecting Subsets of Data11. Boolean Indexing12. Index Alignment13. Grouping for Aggregation, Filtration, and Transformation14. Restructuring Data into a Tidy Form15. Combining Pandas Objects

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