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Edin - Predictive Analytics using Machine Learning 

  • Offered byedX

Predictive Analytics using Machine Learning
 at 
edX 
Overview

Learn how to build predictive models using machine learning.

Duration

38 hours

Total fee

Free

Mode of learning

Online

Schedule type

Self paced

Difficulty level

Intermediate

Credential

Certificate

Predictive Analytics using Machine Learning
 at 
edX 
Highlights

  • 100% Online-Start instantly and learn at your own schedule.
  • Eminent Professor to clear your doubts
  • Pursue a Verified Certificate to highlight the knowledge and skills you gain
  • Self paced Course
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Details Icon

Predictive Analytics using Machine Learning
 at 
edX 
Course details

What are the course deliverables?
  • In this course you will understand the difference between machine learning and other statistical modelsractice building tree-based models, support vector machines and neural networks
  • Implement the theoretic models in machine learning-based software packages in Python
  • Apply machine learning models to business situations
  • Sampling techniques such as bagging and boosting, which improve robustness and overall predictive power, as well as random forests
  • Support vector machines by introducing you to the concept of optimising the separation between classes, before diving into support vector regression
  • Neural networks; their topology, the concepts of weights, biases, and kernels, and optimisation techniques
More about this course
  • This course will give you an overview of machine learning-based approaches for predictive modelling, including tree-based techniques, support vector machines, and neural networks using Python. These models form the basis of cutting-edge analytics tools that are used for image classification, text and sentiment analysis, and more.The course contains two case studies: forecasting customer behaviour after a marketing campaign, and flight delay and cancellation predictions.

Predictive Analytics using Machine Learning
 at 
edX 
Curriculum

Week 1: Decision trees

Week 2: Random forests and support vector machines

Week 3: Support vector machines

Week 4: Neural networks

Week 5: Neural network estimation and pitfalls

Week 6: Model comparison

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Predictive Analytics using Machine Learning
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