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Advanced AI Techniques for the Supply Chain
  • Level Professional
  • المدة 22 ساعات hours
  • الطبع بواسطة LearnQuest
  • Offered by

عن

In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps. We’ll end with a project incorporating advanced techniques with an image classification problem to find faulty products coming out of a machine.

الوحدات

From Basic to Advanced: Models you Need to Know

    • 3 Videos
    • 2 Readings
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3 Videos

  • Course Intro
  • Module Intro
  • Overview of AI methods

2 Readings

  • Supervised and Unsupervised Learning Techniques
  • Forbes: ML Revolutionizing the Supply Chain

Introduction to Neural Networks

    • 1 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Neural Networks

1 Discussions

  • Machine Learning Use Cases

1 Videos

  • Introduction to Neural Networks

1 Readings

  • Neural Networks Playground

Deep Dive into Neural Networks

    • 1 Readings
    • 1 Lab
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1 Labs

  • Implementing Neural Networks

1 Readings

  • Optional: Math Behind Neural Networks

Quiz: Neural Network Basics For the Supply Chain

    • 1 Assignment
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1 Assignment

  • Neural Network Basics For the Supply Chain

Picking a Model

    • 2 Videos
    • 1 Readings
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2 Videos

  • Module Intro
  • Choosing an AI Model

1 Readings

  • Model Selection

Loss Functions and Optimization

    • 1 Videos
    • 1 Readings
    • 1 Lab
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1 Labs

  • Gradient Descent

1 Videos

  • Loss Functions

1 Readings

  • Stochastic Gradient Descent

Overfitting/Underfitting

    • 2 Readings
    • 1 Lab
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1 Labs

  • Overfitting/Underfitting

2 Readings

  • Math Behind Bias-Variance Tradeoff
  • Configuring the Learning Rate

Programming Assignment: Coding Advanced AI Models

    • 1 Lab
    • 1 Programming
    • 1 Assignment
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1 Programming

  • Coding Advanced AI Models

1 Assignment

  • Coding Advanced AI Models

1 Labs

  • P​rogramming Assignment Solutions

Natural Language Preprocessing

    • 2 Videos
    • 2 Readings
    • 1 Lab
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1 Labs

  • Autoencoders

2 Videos

  • Module Intro
  • Autoencoders

2 Readings

  • Accenture: Natural Language Processing Techniques
  • Autoencoders (Optional)

Analyzing Images

    • 2 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Lab
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1 Discussions

  • Automating the ML Pipeline

1 Labs

  • Analyzing Images

2 Videos

  • Notebook Example of Loading Images
  • Notebook Example of CNNs

1 Readings

  • Image Data Analysis Using Python

Making Predictions on Images

    • 1 Videos
    • 2 Readings
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1 Videos

  • Convolutional Neural Networks

2 Readings

  • Convolutional Neural Networks (CNNs)
  • Convolution and Pooling Layers

Quiz: Images and Text

    • 1 Assignment
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1 Assignment

  • Images and Text

PA: Predicting on Images and Text

    • 1 Lab
    • 1 Programming
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1 Programming

  • Predicting Digits Using the MNIST Dataset

1 Labs

  • P​rogramming Assignment Solutions

Auto Summary

Discover cutting-edge AI techniques tailored for the supply chain in this professional-level course by Coursera. Over 1320 minutes, you'll explore advanced machine learning methods, including neural networks and random forests, to predict demand and classify products. Ideal for data science enthusiasts, this course covers essential preprocessing steps and culminates in a hands-on project. Start with a subscription to enhance your AI expertise in supply chain management.

Rajvir Dua
Instructors

Rajvir Dua

Neelesh Tiruviluamala
Instructors

Neelesh Tiruviluamala