Exploratory Data Analysis (EDA) for Machine Learning
Learn the Exploratory Data Analysis Tools with Case studies
What you’ll learn
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You will learn everything you need to know about exploratory data analysis, a method used to analyze and summarize data sets.
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You will gain insights on what should be done with your data set before beginning the work on building ML models
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You will implement data cleaning and validation tasks to get your data ready for data mining activities
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You will learn to estimate parameters and figure the margins of error
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You can understand the structure and content of your data
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You will learn to identify obvious errors, as well as better understand patterns within the data, detect outliers or anomalous events, find interesting relations among the variables.
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You will learn to determine if the statistical techniques you are considering for data analysis are appropriate.
Requirements
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Understanding of Python and basics of machine learning
Who this course is for:
- Data Scientists, Python Programmers, ML Practitioners, IT Managers managing data science projects
