Machine Learning & Data Analytics

Python 3.6.5    |    Intermediate
  • 10 videos | 1h 3m 33s
  • Includes Assessment
  • Earns a Badge
Likes 134 Likes 134
Explore critical machine learning (ML) and deep learning concepts and the various categorizations of algorithms and their implementations using Python.

WHAT YOU WILL LEARN

  • describe the core concepts of machine learning
    identify the critical features and comparable features of machine learning and deep learning
    recognize the correlation and comparable features of machine learning and AI
    set up the development environment for machine learning using Python
    list the various types and techniques of analytics
  • identify the essential benefits of predictive and descriptive analytics
    define the various data metrics that are used to quantify the data for analytics
    classify the various algorithms used in supervised learning
    demonstrate how to implement regression algorithm
    load data set, create data frames, and print the shape of data frames

IN THIS COURSE

  • 5m 34s
    Upon completion of this video, you will be able to describe the core concepts of machine learning. FREE ACCESS
  • 5m 1s
    In this video, you will learn how to identify the critical features and comparable features of machine learning and deep learning. FREE ACCESS
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    3.  Machine Learning and AI Correlation
    4m 35s
    After completing this video, you will be able to recognize the correlation and comparable features of machine learning and AI. FREE ACCESS
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    4.  Installing Python for Machine Learning
    6m 20s
    In this video, you will learn how to set up the development environment for machine learning using Python. FREE ACCESS
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    5.  Analytics Types and Techniques
    5m 49s
    After completing this video, you will be able to list the various types and techniques of analytics. FREE ACCESS
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    6.  Benefits of Predictive and Descriptive Analytics
    2m 27s
    In this video, you will learn how to identify the essential benefits of predictive and descriptive analytics. FREE ACCESS
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    7.  Nominal, Ordinal, Interval, and Ratio Data Metrics
    12m 3s
    Find out how to define the various data metrics that are used to quantify data for analytics. FREE ACCESS
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    8.  Supervised Learning Algorithm
    6m 7s
    In this video, you will learn how to classify the various algorithms used in supervised learning. FREE ACCESS
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    9.  Implementing Regression
    10m 58s
    In this video, you will learn how to implement a regression algorithm. FREE ACCESS
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    10.  Exercise: Working with Data Frames
    4m 38s
    In this video, you will learn how to load a data set, create data frames, and print the shape of data frames. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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