Pandas for Predictive Analysis using scikit-learn [Video]

Video Description

In this course we learn that stand alone data analysis is fine but what most companies these days are looking for is to do Predictive analysis using their data. In this advanced course, we will make you ready to start doing Predictive Analysis on your data by showing you how to build Machine Learning models with scikit-learn and pandas.

In this course, you will be training models and be making data based predictions using scikit-learn.The user will like this as a standalone product as Making Predictions data using Machine Learning is an absolute minimum skill for any Data Analyst \ Data Scientist these days. We will teach users how to use scikit-learn to make data based predictions. User will learn how to bring in their data using pandas, apply some machine learning models and take out the predictions. We will also walk the user through various popular Machine Learning algorithms.

By the end of this course, the user will be quite confident of doing Predictive Analysis on their own. This subject matter is big enough that 2-3 hours of stand alone course is the absolute bare minimum to achieve it.

Style and Approach

In this course, you will learn how to apply machine learning models and make predictions as a Data scientist with the help of real world examples.

What You Will Learn

• Learn to read different kinds of data into Pandas Dataframes for data analysis.
• Discover how to manipulate, transform and apply formulas on the data imported into the pandas dataframes
• See how to analyze and visualize different kinds of data using Pandas, to gain real world insights.
• Get to know how to use Pandas to make predictions using Machine Learning and scikit-learn
• Work with Big Data using Pandas, and get useful information for your business decisions
• Practice data analysis with quantitative financial data and see how to model time-series data, perform algorithmic trading
• Take your Pandas to the next level by learning advanced techniques.
• Get to know how to take out transformed data out of Pandas dataframes and into the formats your application expects.

Authors: Harish Garg

Harish Garg is a Data Analyst, author, and Software Developer who is really passionate about Data Science and the Python programming language. He is a graduate from Udacity's Data Analyst Nanodegree program. He has 17 years of industry experience, which includes data analysis using Python, developing and testing enterprise and consumer software, managing projects and software teams, and creating training material and tutorials. Harish also worked for 11 years for Intel Security (previously McAfee, Inc.).

He regularly contributes articles and tutorials on data analysis and Python. He is also active in the open data community and is a contributing member of the Data4Democracy open data initiative. He has written data analysis pieces for think tan takshashila.

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