Unsupervised Machine Learning in Python
  • ondemand_video
       Video Length : 6h30m0s
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       Tasks Number : 44
  • group
       Students Enrolled : 667
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       Medium Level
  • Curriculum
  • 1. Introduction to Unsupervised Learning
    • videocam
      Introduction and Outline
      10m0s
    • videocam
      What is unsupervised learning?
      10m0s
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      Why Use Clustering?
      10m0s
    • videocam
      How to Succeed in this Course
      10m0s
  • 2. K-Means Clustering
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      An Easy Introduction to K-Means Clustering
      10m0s
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      Visual Walkthrough of the K-Means Clustering Algorithm
      10m0s
    • videocam
      Soft K-Means
      10m0s
    • videocam
      The K-Means Objective Function
      10m0s
    • videocam
      Soft K-Means in Python Code
      10m0s
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      Visualizing Each Step of K-Means
      10m0s
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      Examples of where K-Means can fail
      10m0s
    • videocam
      Disadvantages of K-Means Clustering
      10m0s
    • videocam
      How to Evaluate a Clustering (Purity, Davies-Bouldin Index)
      10m0s
    • videocam
      Using K-Means on Real Data: MNIST
      10m0s
    • videocam
      One Way to Choose K
      10m0s
    • videocam
      K-Means Application: Finding Clusters of Related Words
      10m0s
  • 3. Hierarchical Clustering
    • videocam
      Visual Walkthrough of Agglomerative Hierarchical Clustering
      10m0s
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      Agglomerative Clustering Options
      10m0s
    • videocam
      Using Hierarchical Clustering in Python and Interpreting the Dendrogram
      10m0s
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      Application: Evolution
      10m0s
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      Application: Donald Trump vs. Hillary Clinton Tweets
      10m0s
  • 4. Gaussian Mixture Models (GMMs)
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      Description of the Gaussian Mixture Model and How to Train a GMM
      10m0s
    • videocam
      Comparison between GMM and K-Means
      10m0s
    • videocam
      Write a Gaussian Mixture Model in Python Code
      10m0s
    • videocam
      Practical Issues with GMM / Singular Covariance
      10m0s
    • videocam
      Kernel Density Estimation
      10m0s
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      Expectation-Maximization
      10m0s
    • videocam
      Future Unsupervised Learning Algorithms You Will Learn
      10m0s
  • 5. Appendix
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      What is the Appendix?
      10m0s
    • videocam
      Windows-Focused Environment Setup 2018
      10m0s
    • videocam
      How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow
      10m0s
    • videocam
      How to Code by Yourself (part 1)
      10m0s
    • videocam
      How to Code by Yourself (part 2)
      10m0s
    • videocam
      How to Succeed in this Course (Long Version)
      10m0s
    • videocam
      Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
      10m0s
    • videocam
      Proof that using Jupyter Notebook is the same as not using it
      10m0s
    • videocam
      Python 2 vs Python 3
      10m0s
    • videocam
      What order should I take your courses in? (part 1)
      10m0s
    • videocam
      What order should I take your courses in? (part 2)
      10m0s
Authors

Kevin Gautama is a systems design and programming engineer with 16 years of expertise in the fields of electrical and electronics and information technology.

He teaches at the Hanoi University of Industry in the period 2003-2011 and he has a certificate of vocational training by the Ministry of Industry and Commerce and the Hanoi University of Industry.

From extensive design experience through numerous engineering projects, the author founded the Enziin Academy.

The Enziin Academy is a startup in the field of educational, it's core goal is to training design engineers in the fields technology related.

The Enziin Academy is headquartered in Stockholm-Sweden with an orientation operating multi-lingual and global.

The author's skills in IT:

  • Implementing the application infrastructure on Amazon's cloud computing platform.
  • Linux server system administration (Sysadmin).
  • Design load balancing and content distribution system.
  • MySQL database administration.
  • C/C++/C# Programming
  • Ruby and Ruby on Rails Programming
  • Python and Django Programming
  • The WPF/C# on the .NET Framework Programming
  • The PHP/JAVA Programming
  • Machine Learning and Expert System.
  • Internet of Things.

The author's skills in the fields of electric and electronic:

  • The design of popular CPU / MCU systems.
  • Design FPGA / CPLD system (Xilinx - Altera).
  • Design and programming of DSP systems (Texas Instruments).
  • Embedded ARM system design.
  • The RTOS Programming
  • Design and programming electronic power systems.
  • PLC - inverter - sensor - electric control cabinet industrial.
  • Control systems distributed connection with Server.

Read more...

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Unsupervised Machine Learning in Python


Unsupervised Machine Learning in Python

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