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Predictive Analytics using Machine Learning

Predictive Analytics using Machine Learning

Learn how to build predictive models using machine learning.

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Course Highlights

  • Self-directed and active ways of learning: reading, coding in Python, knowledge check quizzes,and peer discussion.

  • Eminent Professor to clear your doubts

  • Pursue a Verified Certificate to highlight the knowledge and skills you gain

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7 Day Exchange Policy

Validity: 42 Days

Mode of learning: Online self study

Course Overview

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.

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