Real-World Machine Learning Projects with Scikit-Learn

Video Description

Predict heart disease, customer-buying behaviors, and much more in this course filled with real-world projects

About This Video

  • Observe data from multiple angles and use machine learning algorithms to solve real-world problem to make your projects successful.
  • Use Regression Trees, Support Vector Machines, K-Means Clustering, and customer segmentation algorithms in real world situations.
  • Apply your knowledge to practical real-world projects using ML models to get insightful solutions

In Detail

Scikit-Learn is one of the most powerful Python Libraries with has a clean API, and is robust, fast and easy to use. It solves real-world problems in the areas of health, population analysis, and figuring out buying behavior, and more.

In this course you will build powerful projects using Scikit-Learn. Using algorithms, you will learn to read trends in the market to address market demand. You'll delve more deeply to decode buying behavior using Classification algorithms; cluster the population of a place to gain insights into using K-Means Clustering; and create a model using Support Vector Machine classifiers to predict heart disease.

By the end of the course you will be adept at working on professional projects using Scikit-Learn and Machine Learning algorithms.

The code bundle for this video course is available at - https://github.com/PacktPublishing/Real-World-Machine-Learning-Projects-with-Scikit-Learn

Product Information

  • Title: Real-World Machine Learning Projects with Scikit-Learn
  • Author(s): Nikola Živković
  • Release date: August 2018
  • Publisher(s): Packt Publishing
  • ISBN: 9781789131222