Data Visualization using plotly, matplotlib, seaborn and squarify

Data Visualization is one of the important activity we perform when doing Exploratory Data Analysis. It helps in preparing business reports, visual dashboards, story telling etc important tasks. In this post I have explained how to ask questions from the data and in return get the self explanatory graphs. In this You will learn the use of various python libraries like plotly, matplotlib, seaborn, squarify etc to plot those graphs.

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A Complete Guide to Principal Component Analysis – PCA in Machine Learning

Principal Component Analysis or PCA is a widely used technique for dimensionality reduction of the large data set. Reducing the number of components or features costs some accuracy and on the other hand, it makes the large data set simpler, easy to explore and visualize. Also, it reduces the computational complexity of the model which makes machine learning algorithms run faster. It is always a question and debatable how much accuracy it is sacrificing to get less complex and reduced dimensions data set. we don’t have a fixed answer for this however we try to keep most of the variance while choosing the final set of components.

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