Vrushali Lanjewar

A graphical depiction of information and data is characterized as data visualization. Data visualization approaches use visual components like charts, graphs, and maps to give an easy way to observe and comprehend trends, outliers, and patterns in data.

Steps to follow:

1. Data visualizations should have a clear purpose and target audience.

2. Select the appropriate sort of visualization or chart for your data.

3. Use text and labels to clarify rather than to clutter.

4. Use color to highlight significant information, differentiate or compare it, or to differentiate or compare it.

5. Avoid using deceptive visuals.

Google Charts, Tableau, Grafana, Chartist. js, FusionCharts, Datawrapper, Infogram, ChartBlocks, and D3. js are among the greatest data visualization tools. The finest tools provide a wide range of visualization techniques, are simple to use, and can handle massive data sets.

Use the following link to understand the various data analytics techniques:

https://www.analyticsvidhya.com/blog/2021/08/effective-data-visualization-techniques-in-data-science-using-python/

Visualization techniques and tools: learn how to practice visualization

• Create a vision board. This visualization tool is a collection of images and words that inspire you and represent your goals.
• Listen to a guided visualization meditation.
• Use index cards.
• Picture and describe.
• Utilize exposure.

DEAR Vrushali Lanjewar

Use the following link to consider that proper for your question:

1-Data Visualization Techniques and Algorithms,DOI:10.1007/978-981-15-6695-0_10,In book: Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing

2-Data Visualization Techniques, Model and Taxonomy,DOI:10.1007/978-3-030-25797-2_11,In book: Data Visualization and Knowledge Engineering

GOOD LUCK

I think that Random forest.

Data Visualization Techniques in Data Science: I. Line Chart · II.Histogram · III.Pie Chart · IV. Area plot · V. Scatter plots · VI. Hexbins plots · VII. Heatmap.

I think heatmap of confusion matrix is good technique for data visualization.

There are many ways how you can do it, and all depends on the data, your goals and target audience.

I would recommend to start from here:

https://www.data-to-viz.com/