Supervised Learning Essential Training

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Free Online Course: Supervised Learning Essential Training provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Supervised Learning Essential Training is taught by Ayodele Odubela.

Overview
  • This mid-level course takes you through how to create one of the most common types of machine learning: supervised learning models.

Syllabus
  • Introduction

    • Supervised machine learning and the technology boom
    • Using the exercise files
    • What you should know
    1. Supervised Learning with Python
    • What is supervised learning?
    • Python supervised learning packages
    • Predicting with supervised learning
    2. Regression Modeling
    • Defining logistic and linear regression
    • Steps to prepare data for modeling
    • Checking your dataset for assumptions
    • Creating a linear regression model
    • Creating a logistic regression model
    • Evaluating regression model predictions
    3. Decision Trees
    • Identify common decision trees
    • Splitting data and limiting decision tree depth
    • How to build a decision tree
    • Creating your first decision trees
    • Analyzing decision tree performance
    • Exploring how ensemble methods create strong learners
    4. K-Nearest Neighbors
    • Discovering your k-nearest neighbors
    • What's the big deal about k
    • How to assemble a KNN model
    • Building your own KNN
    • Deciphering KNN model metrics
    • Searching for the best model
    5. Neural Networks
    • Biological vs. artificial neural networks
    • Preprocessing data for modeling
    • How neural networks find patterns in data
    • Assembling your neural networks
    • Comparing networks and selecting final models
    Conclusion
    • Ethical overview
    • How can I keep developing my skills in supervised learning?