Pandas for Predictive Analysis using scikit-learn
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Pandas for Predictive Analysis using scikit-learn

Learn how to use Pandas for Predictive Analysis by employing scikit-learn
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0.0 (0 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1 student enrolled
Created by Packt Publishing
Last updated 9/2017
English
English [Auto-generated]
Current price: $10 Original price: $125 Discount: 92% off
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Includes:
  • 1 hour on-demand video
  • 1 Supplemental Resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I 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.
View Curriculum
Requirements
  • Some programming experience in Python will be helpful to get the most out of this course. You will also see 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. You will learn how to read different kinds of data into Pandas Dataframes for data analysis.
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 absolute bare minimum to achieve it.

About the author

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.

Who is the target audience?
  • If you are a budding data scientist looking to learn the popular pandas library, or a Python developer looking to step into the world of data analysis, this video is the ideal resource you need to get started.
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Curriculum For This Course
14 Lectures
01:12:46
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Setting Up scikit-learn and Training Your First ML Model
5 Lectures 24:43

This video provides an overview of the entire course.

Preview 03:24

This video will introduce the scikit-learn library, how to install it, and verify the setup.

Setting Up scikit-learn for Machine Learning
02:49

Learn how to load and process internal and external datasets into scikit-learn.

Preprocessing Your Data to Make It Ready for Training a Model
08:11

Learn how to train and run a classification model.

Training and Running the Classification Model
04:20

This video explores how to load, clean and process your data to make it ready for machine learning models in scikit-learn.

Getting Your Own Data Ready for Machine Learning
05:59

Test your knowledge
8 questions
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Choosing and Evaluating Best ML Models
3 Lectures 14:59

Learn how to Evaluate performance and accuracy of a machine learning model.

Preview 04:11

Explore different ways to select the best features for building a machine learning model with high accuracy. 

Selecting Best Features for Training the Model
04:31

Learn how to tune features in a machine learning model for the best performance and accuracy.

Tuning Feature Performance
06:17

Test your knowledge
6 questions
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Trying Out Some Different scikit-learn Algorithms
3 Lectures 14:25

Learn how to train and run Naive Bayes classifiers.

Preview 05:18

Explore how to build machine learning using Support Vector Machine algorithm.

Building Models Using Support Vector Machine
02:49

Learn how to use Decision Tree classifiers for machine learning.

Using Decision Tree Classifiers
06:18

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Learn how to build and train machine learning model on your corpus of text using scikit-learn.

Building and Training a Model
03:55

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Making Predictions
05:42

Test your knowledge
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About the Instructor
Packt Publishing
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58,756 Students
686 Courses
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