This course facilitates major part of a data science project activity. In reality data scientists spend much of their time transforming, shaping-reshaping data to serve to several machine learning models. The activity to clean, transform and process the data will be the prime focus of this program. This program will also demonstrate simple to complex data visualizations using Pandas visualization library, seaborn library and matplotLib.
Numpy will be used to convert series data into N-dimensional arrays to feed into predictive models. Random numbers, math operations and statistics using Numpy will also be featured.
TECHNOLOGY USED: Python General Purpose, Anaconda Jupyter Notebooks, Pandas, Numpy
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