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Effective Prediction with Machine Learning - Second Edition

Video Description

A one-stop solution to quickly program fast Machine Learning algorithms with NumPy and scikit-learn

About This Video

  • Plot different shapes using NumPy and matplotlib, making the visualization more appealing
  • Imputing missing values through various strategies
  • Use Gaussian processes for regression

In Detail

Scikit-learn has evolved as a robust library for machine learning applications in Python with support for a wide range of supervised and unsupervised learning algorithms.

This course begins by taking you through videos on evaluating the statistical properties of data and generating synthetic data for machine learning modeling. As you progress through the sections, you will come across videos that will teach you to implement techniques such as data pre-processing, linear regression, logistic regression, and K-NN. You will also look at Pre-Model and Pre-Processing workflows, to help you choose the right models.

Finally, you'll explore dimensionality reduction with various parameters.