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Learn web scraping and data mining from scratch using Python

Learn data preprocessing, data wrangling, and data visualization for hands-on data science and data analytics applications in R

Data wrangling and data visualization with the Tidyverse R data science package

Decision trees and ensembling techinques in R studio. Bagging, random forest, GBM, AdaBoost and XGBoost in R programming

Discover the story of your data using the essential elements of associations and correlations

Explore the different data mining techniques using the libraries and packages offered by Python

Web Scraping techniques are getting more popular, since data is as valuable as oil in 21st century. Through this book get some key knowledge about using XPath, regEX; web scraping libraries for R like rvest and RSelenium technologies.

Over-fetching and under-fetching data affect the performance of your web applications. Learn to define the API structure and handle data requirement using types and schemas of GraphQL to build smart APIs that enhance your applications.

Get high-quality information from your text using Machine Learning with Tensorflow, NLTK, Scikit-Learn, and Python

Untangle your web scraping complexities and access web data with ease using Python scripts

Enter the world of Statistics, Data Analysis and Data Science!

Mine valuable insights from your data using popular tools and techniques in R

Successfully scrape data from any website with the power of Python 3.x

Harness the power of Python to develop data mining applications, analyze data, delve into machine learning, explore object detection using Deep Neural Networks, and create insightful predictive models.

See the in-depth capabilities of Python’s web scraping tools