Training Your Systems with Python Statistical Modeling

Book cover

This video course, published with Packt Publishing, is an introductory course for data analysis with Python. This course discusses how to use Python for machine learning. The course covers

  • Classical statistical methods (from both frequentist and Bayesian perspectives)
  • Supervised learning methods, with models ranging from decision trees to neural networks
  • Classification and regression
  • Clustering
  • Dimensionality reduction
  • And more!

The course is peppered with examples demonstrating the techniques and software on real-world data and visuals to explain the concepts presented. Viewers get a hands-on experience using Python for machine learning.

This course is the third volume in a four-volume series entitled, Taming Data with Python; Excelling as a Data Analyst. The first volume of the course, Unpacking NumPy and Pandas, discussed setting up a Python data analysis environment and introductory usage of NumPy and Pandas. The second volume, Data Acquisition and Manipulation with Python, showed how to perform more advanced data manipulation with Pandas and how to get data from the Internet. The final volume gives example applications.

Packt Publishing has made some of the videos included in the course available on YouTube. You can watch these to get an idea of what’s in the course.

Read more and purchase the course at Packt Publishing’s website. Also, you can read my blog post announcing the course’s publication.