Supervised, Unsupervised & Deep Learning

Python 3.6.5
  • 10 Videos | 1h 35m 7s
  • Includes Assessment
  • Earns a Badge
Likes 39 Likes 39
Discover how to implement various supervised and unsupervised algorithms of machine learning using Python, with the primary focus of clustering and classification.

WHAT YOU WILL LEARN

  • demonstrate how to implement classification
    list the various types of algorithms used in unsupervised learning
    demonstrate how to implement K-Mean clustering
    demonstrate how to implement hierarchical clustering
    demonstrate how to facilitate text mining and work with recommender systems
  • demonstrate the process involved in text mining and data assembly
    specify the concepts of deep and reinforcement learning
    work with Restricted Boltzmann machines
    build models using Convolution Neural Network
    utilize data frames and centroids

IN THIS COURSE

  • Playable
    1. 
    Working with Classification
    10m 7s
    UP NEXT
  • Playable
    2. 
    Unsupervised Learning
    5m 55s
  • Locked
    3. 
    K-Mean Clustering
    14m 50s
  • Locked
    4. 
    Hierarchical Clustering
    12m 9s
  • Locked
    5. 
    Text Mining and Recommender Systems
    11m 1s
  • Locked
    6. 
    Text Mining and Data Assembly
    9m 7s
  • Locked
    7. 
    Deep and Reinforcement Learning Concepts
    6m 27s
  • Locked
    8. 
    Restricted Boltzmann
    5m 36s
  • Locked
    9. 
    Working with CNN
    9m 13s
  • Locked
    10. 
    Exercise: Working with Data Frames and Centroids
    6m 11s

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