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Machine Learning Essentials with Python and Spark is a foundation-level, three-day hands-on course that teaches you core skills and concepts in modern machine learning at scale practices, leveraging Python and Spark.
Unlimited Duration
March 3, 2021
This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. In this course you will learn about:
• Machine Learning (ML) Overview
• Machine Learning in Python and Spark
• Machine Learning Concepts
• Feature Engineering (FE)
• Linear regression
• Logistic Regression
• Classification: SVM (Supervised Vector Machines)
• Classification: Decision Trees & Random Forests
• Classification: Naive Bayes
• Clustering (K-Means)
• Principal Component Analysis (PCA)
• Recommendations (Collaborative filtering)
• Performance
• Time Permitting: Capstone Project
Course Curriculum
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- Machine Learning landscape 00:00:00
- Machine Learning applications 00:00:00
- Understanding ML algorithms & models 00:00:00
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- Spark ML Overview 00:00:00
- Introduction to Jupyter notebooks 00:00:00
- Working with Jupyter + Python + Spark 00:00:00
- Statistics Primer 00:00:00
- Covariance, Correlation, Covariance Matrix 00:00:00
- Errors, Residuals 00:00:00
- Overfitting / Underfitting 00:00:00
- Cross-validation, bootstrapping 00:00:00
- Confusion Matrix 00:00:00
- ROC curve, Area Under Curve (AUC) 00:00:00
- Simple Linear Regression 00:00:00
- Multiple Linear Regression 00:00:00
- Running LR 00:00:00
- Evaluating LR model performance 00:00:00
- Use case: House price estimates 00:00:00
- SVM concepts and theory 00:00:00
- SVM with kernel 00:00:00
- Use case: Customer churn data 00:00:00
- Theory 00:00:00
- Use case: spam filtering 00:00:00
- Understanding PCA concepts 00:00:00
- PCA applications 00:00:00
- Running a PCA algorithm 00:00:00
- Evaluating results 00:00:00
- Use case: analyzing retail shopping data 00:00:00
- Best practices for scaling and optimizing Apache Spark 00:00:00
- Memory caching 00:00:00
- Testing and validation 00:00:00
Course Reviews
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