Data Analytics With Python

Data is a collection of facts and information. Data analysis is transformation & organizing data to draw conclusions and predictions to use for decision making. Data can be produced by humans or machines like smart devices and digital products(Facebook, Google, Youtube), etc. 

These are the stages of data analysis:

• Ask
• Prepare
• Process
• Analyze 
• Shara
• Act

We use Excel spreadsheet, SQL to store data, and Python libraries like NumPy, Panda, Metplotlib, etc to analyze data and data visualization tools like MS Power BI, Tableau, Rstudion, Google studio to visualize the data.

Python libraries:

• Pandas & Numpy are used for scientific & mathematical calculations
• Metplotlib for visualization in the form of plots and graphs.
• Seaborn for heat mat, time-series plotting
• Scikit-learn for ML and statistical modeling, regression, and classification (Built on Numpy, sci-py, and metplotlib
• Keras - Deep learning
• Tensorflow - ML and DL predictions model development