Supervised, Unsupervised & Deep Learning

Python    |    Intermediate
  • 10 videos | 1h 30m 37s
  • Includes Assessment
  • Earns a Badge
Rating 4.5 of 258 users Rating 4.5 of 258 users (258)
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

  • 10m 7s
    In this video, you will learn how to implement a classification. FREE ACCESS
  • 5m 55s
    Upon completion of this video, you will be able to list the various types of algorithms used in unsupervised learning. FREE ACCESS
  • Locked
    3.  K-Mean Clustering
    14m 50s
    In this video, you will learn how to implement K-Means clustering. FREE ACCESS
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    4.  Hierarchical Clustering
    12m 9s
    In this video, you will learn how to implement hierarchical clustering using the SciPy library. FREE ACCESS
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    5.  Text Mining and Recommender Systems
    11m 1s
    In this video, you will learn how to text mine and work with recommender systems. FREE ACCESS
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    6.  Text Mining and Data Assembly
    9m 7s
    In this video, you will learn how to apply the process involved in text mining and data assembly. FREE ACCESS
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    7.  Deep and Reinforcement Learning Concepts
    6m 27s
    Upon completion of this video, you will be able to specify the concepts of deep and reinforcement learning. FREE ACCESS
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    8.  Restricted Boltzmann
    5m 36s
    During this video, you will learn how to work with Restricted Boltzmann Machines. FREE ACCESS
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    9.  Working with CNN
    9m 13s
    In this video, you will build models using a Convolution Neural Network. FREE ACCESS
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    10.  Exercise: Working with Data Frames and Centroids
    6m 11s
    In this video, find out how to use data frames and centroids. FREE ACCESS

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