Machine & Deep Learning Algorithms: Introduction

Machine Learning    |    Beginner
  • 7 Videos | 47m 49s
  • Includes Assessment
  • Earns a Badge
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Examine fundamentals of machine learning (ML) and how Pandas ML can be used to build ML models in this 7-video course. The working of Support Vector Machines to perform classification of data are also covered. Begin by learning about different kinds of machine learning algorithms, such as regression, classification, and clustering, as well as their specific applications. Then look at the process involved in learning relationships between input and output during the training phase of ML. This leads to an introduction to Pandas ML, and the benefits of combining Pandas, scikit-learn, and XGBoost into a single library to ease the task of building and evaluating ML models. You will learn about Support Vector Machines, which are a supervised machine learning algorithm, and how they are used to find a hyperplane to divide data points into categories. Learners then study the concept of overfitting in machine learning, and the problems associated with a model overfitted to training data. and how to mitigate the issue. The course concludes with an exercise in machine learning and classification.

WHAT YOU WILL LEARN

  • recognize the different kinds of machine learning algorithms such as regression, classification, and clustering, as well as their specific applications
    describe the process involved in learning a relationship between input and output during the training phase of machine learning
    identify the benefits of combining Pandas, scikit-learn, and XGBoost into a single library to ease the task of building and evaluating ML models
  • describe what Support Vector Machines are and how they are used to find a hyperplane to divide data points into categories
    recognize the problems associated with a model that is overfitted to training data and how to mitigate the issue
    define what unsupervised learning is, list the features of SVMs, and describe the issues one may run into when using an overfitted model for predictions

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 58s
    UP NEXT
  • Playable
    2. 
    Machine Learning Algorithms
    8m 39s
  • Locked
    3. 
    How Machine Learning Works
    7m 19s
  • Locked
    4. 
    Introduction to Pandas ML
    5m 45s
  • Locked
    5. 
    Support Vector Machines
    6m 7s
  • Locked
    6. 
    Overfitting
    7m 48s
  • Locked
    7. 
    Exercise: Machine Learning and Classification
    7m 44s

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