deepsparkchaker / data-evaluation

Data Science Guide:

Cross-industry standard process for data mining, known as CRISP-DM, is an open standard process model that describes common approaches used by data mining experts. It is the most widely-used analytics mode.

CRISP-DM breaks the process of data mining into six major phases:

Business Understanding
Data Understanding
Data Preparation
Modeling
Evaluation
Deployment

The sequence of the phases is not strict and moving back and forth between different phases as it is always required. ==>The objective is to share a real guide to master the science of data from 0 to hero:

• Master Python for Data science

• EDA

• Modeling Machine learning Algorithms Using (Regression , Classification..)

• NLP

• Big Data Analytics tools(spark)

• ......and many more

1- Data visualization

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data.

In the world of Big Data, data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions. Common general types of data visualization:

Charts
Tables
Graphs
Maps
Infographics
Dashboards

More specific examples of methods to visualize data:

Area Chart
Bar Chart
Box-and-whisker Plots
Bubble Cloud
Bullet Graph
Cartogram
Circle View
Dot Distribution Map
Gantt Chart
Heat Map
Highlight Table
Histogram
Matrix
Network
Polar Area
Radial Tree
Scatter Plot (2D or 3D)
Streamgraph
Text Tables
Timeline
Treemap
Wedge Stack Graph
Word Cloud
And any mix-and-match combination in a dashboard!