Course curriculum

    1. Unsupervised Learning

    2. Why Do We Need Dimensionality Reduction?

    3. Principal Component Analysis (PCA)

    4. PCA for Data Visualization

    5. PCA for Data Visualization Exercise (Practice)

    6. PCA for Supervised Machine Learning

    7. PCA Exercise(core)

    8. Feature Engineering: Overloaded Operators

    9. Feature Engineering: Strings

    10. Feature Engineering: Datetime

    11. Feature Engineering: Functions

    12. Feature Engineering Exercise (Core)

    13. Feature Selection

    14. Feature Selection 2

    15. Feature Selection (Practice)

    16. Project 4 - Part 1 (Core)

    17. Interview Questions (Optional)

    18. Optional - Dimensionality Reduction Resources

    1. KMeans Clustering

    2. KMeans Clustering in Python

    3. Clustering Evaluation Metrics

    4. PCA to Visualize Clusters (Practice)

    5. Explanatory Analysis of KMeans Clusters

    6. KMeans Clustering (Core)

    7. Project 4 - Part 2 (Core):

    8. Intro to Anomaly Detection

    9. Anomaly Detection (Core)

    10. Clustering Interview Questions

    11. Optional Resources

    1. Introduction to Deep Learning

    2. How Neurons Learn

    3. Forward Propagation

    4. Conceptual Neural Network (Practice)

    5. Why Use Activation Functions?

    6. Backward Propagation

    7. Intro to Keras

    8. Adding More Metrics

    9. Simple Neural Networks (Practice)

    10. Bias and Variance in Deep Learning

    11. Deep Learning Regularization

    12. Early Stopping

    13. Keras Tuner

    14. Regression Models in Keras

    15. Binary Classification Models in Keras

    16. Multiclass Classification in Keras

    17. Neural Network Exercise (Core)

    18. Project 4 - Part 3 (Core)

    19. Interview Questions

    20. ADMINOptional - How a Neural Network Works

    21. IMAGES-NEURAL NETWORK

    1. Welcome to Belt Exam Prep!

    2. Belt Exam Rules and Policies

    3. Mock Belt Exam (Practice)

    1. Intro to CNNs

    2. Working with Images

    3. CNNs in Python

    1. Exam grading system

    2. How to submit the exam?

    3. Intermediate ML Belt Exam (Retake)

About this course

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  • 59 lessons
  • 0 hours of video content

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