Create Your Own Sophisticated Model with Neural Networks [Video]
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.
With this course you will learn the Decision Tree algorithms and Ensemble Models to build Random Forest, Regression Analysis. You will focus on Decision Trees and Ensemble Algorithms. Moving forward, you learn to use scikit-learn to classify text and Multiclass with scikit-learn. You will explore various algorithms for classification. You will also look at Naive Bayes model and Label Propagation. Finally, you'll use Neural Networks using different Classifiers and create your own Simple Estimator.
Style and Approach
This course consists of practical scikit-learn videos that target novices as well as intermediate users. It explores technical issues in depth, covers additional protocols, and supplies many real-life examples so that you are able to implement scikit-learn in your daily life.
|Course Length||1 hour 24 minutes|
|Date Of Publication||27 Mar 2018|