Machine Learning Crash Course with TensorFlow APIs

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Free Online Course: Machine Learning Crash Course with TensorFlow APIs provided by Independent is a comprehensive online course, which lasts for 15 hours worth of material. The course is taught in English and is free of charge.

Overview
  • A self-study guide for aspiring machine learning practitioners. Machine Learning Crash Course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises.

    Some of the questions answered in this course:

    • Learn best practices from Google experts on key machine learning concepts.
    • How does machine learning differ from traditional programming?
    • What is loss, and how do I measure it?
    • How does gradient descent work?
    • How do I determine whether my model is effective?
    • How do I represent my data so that a program can learn from it?
    • How do I build a deep neural network?

Syllabus
  • ML Concepts

    • Introduction
    • Framing
    • Descending into ML
    • Reducing Loss
    • First Steps with TF
    • Generalization
    • Training and Test Sets
    • Validation
    • Representation
    • Feature Crosses
    • Regularization: Simplicity
    • Logistic Regression
    • Classification
    • Regularization: Sparsity
    • Introduction to Neural Nets
    • Training Neural Nets
    • Multi-Class Neural Nets
    • Embeddings

    ML Engineering

    • Production ML Systems
    • Static vs Dynamic Training
    • Static vs Dynamic Inference
    • Data Dependencies

    ML Real World Examples

    • Cancer Prediction
    • 18th Century Literature
    • Real-World Guidelines

    Conclusion

    • Next Steps