These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of these guides are available.
Twin brothers and educators Afshine and Shervine Amidi, creators of past fantastic machine learning and deep learning study resources, are back and at it again, this time with a set of illustrated study guides for an array of data science tools.
This set of illustrated study guides for data science tools was born out of an MIT class that Afshine is currently teaching, though the brothers created the resources in tandem.
What exactly is covered in these guides? They are broken up into four distinct categories, each category containing between one and three individual related guides. The below links redirect to the online versions of these guides; PDF versions are available further below.
Concepts covered in this guide include: filtering, conditions and data types; types of joins; aggregations, window functions; table manipulation
Concepts covered in these guides include: filtering, conditions and data types; types of joins; aggregations, window functions; data frame transformations; conversions made easy between R and Python
Concepts covered in these guides include: scatterplots, line plots, histograms; boxplots, maps; customized legend; conversion made easy between R and Python
SQL stands for Structured Query Language. SQL is a scripting language expected to store, control, and inquiry information put away in social databases. The main manifestation of SQL showed up in 1974, when a gathering in IBM built up the principal model of a social database. The primary business social database was discharged by Relational Software later turning out to be Oracle.
🔵 Intellipaat Data Science with Python course: https://intellipaat.com/python-for-data-science-training/In this Data Science With Python Training video, you...
Data Visualization in R with ggplot2: A Beginner Tutorial. Learn to visualize your data using R and ggplot2 in this beginner-friendly tutorial that walks you through building a chart for data analysis.
Learn the essential concepts in data science and understand the important packages in R for data science. You will look at some of the widely used data science algorithms such as Linear regression, logistic regression, decision trees, random forest, including time-series analysis. Finally, you will get an idea about the Salary structure, Skills, Jobs, and resume of a data scientist.
🔥Intellipaat Python for Data Science Course: https://intellipaat.com/python-for-data-science-training/In this python for data science video you will learn e...