Network analysis with networks - Python Tutorial

Contents

• Introduction Introduction

  • Artificial intelligence and human resources

    1m 22s
  • Course prerequisites

    1m
• 1. Human Resources and AI 1. Human Resources and AI

  • Introduction to HR

    2m 2s
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    HR challenges

    1m 9s
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    AI and HR

    3m 8s
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    HR use cases overview

    2m 17s
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    Setting up the exercise files

    2m 7s
• 2. Use Case 1: Predicting Employee Attrition 2. Use Case 1: Predicting Employee Attrition

  • Employee attrition

    1m 37s
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    Classification with deep learning

    1m 15s
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    Data for employee attrition

    1m 41s
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    Preprocessing attrition data

    2m 17s
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    Building an attrition model with Keras

    1m 32s
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    Predicting attrition with Keras

    1m 1s
• 3. Use Case 2: Discovering Collaboration 3. Use Case 2: Discovering Collaboration

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    Organization design

    2m 18s
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    Network analysis with networks

    2m 24s
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    Data for network analysis

    59s
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    Preparing network data

    1m 59s
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    Creating and visualizing networks

    2m 6s
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    Analyzing networks

    2m 24s
• 4. Use Case 3: Recommend Training Courses 4. Use Case 3: Recommend Training Courses

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    Employee development

    1m 8s
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    User item recommendations

    1m 34s
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    Ratings data for recommendations

    51s
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    Prepare for embedding

    2m 10s
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    Building a Keras rating model

    2m 22s
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    Recommending courses with Keras

    2m 34s
• 5. Other HR Use Cases 5. Other HR Use Cases

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    Predict future employee performance

    2m 42s
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    Candidate outreach

    2m 31s
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    Automated candidate screening

    2m 29s
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    Employee virtual assistant

    2m 15s
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    Sentiment analysis

    2m 1s
• 6. Generative AI for HR 6. Generative AI for HR

  • Generative AI review

    2m 25s
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    Text generation with LLMs

    1m 39s
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    Resume summarization

    2m 17s
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    Job description generation

    2m 12s
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    Employee self-help chatbot

    2m 48s
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    Resume skills extraction

    1m 54s
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    Resume skills extraction example

    2m 52s
• 7. IT Ops Best Practices 7. IT Ops Best Practices

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    Model development best practices

    1m 27s
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    Using machine learning platforms

    1m 18s
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    Model serving best practices

    1m 31s
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    Security and privacy best practices

    1m 26s
• Conclusion Conclusion

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    Next steps

    39s