Authoring Machine Learning Models from Scratch

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1. Introduction
• 1. Introduction-en_US.srt (2.4 KB)
• 1. Introduction.mp4 (23.1 MB)
• 2. What is this course... exactly-en_US.srt (1.8 KB)
• 2. What is this course... exactly.mp4 (1.8 MB)
• 3. Course Outcomes-en_US.srt (2.2 KB)
• 3. Course Outcomes.mp4 (10.2 MB)
• 4. Course Structure-en_US.srt (1.8 KB)
• 4. Course Structure.mp4 (1.8 MB)
• 5. What is an Algorithm in Programming-en_US.srt (4.1 KB)
• 5. What is an Algorithm in Programming.mp4 (25.4 MB)
2. Data Preparation
• 1. Loading Data from a CSV File-en_US.srt (6.1 KB)
• 1. Loading Data from a CSV File.mp4 (28.1 MB)
• 10. Classification Accuracy-en_US.srt (2.0 KB)
• 10. Classification Accuracy.mp4 (7.7 MB)
• 11. Confusion Matrix-en_US.srt (4.5 KB)
• 11. Confusion Matrix.mp4 (12.5 MB)
• 12. Regression Metrics-en_US.srt (3.6 KB)
• 12. Regression Metrics.mp4 (18.0 MB)
• 13. Baseline Models-en_US.srt (1.8 KB)
• 13. Baseline Models.mp4 (18.3 MB)
• 14. Random Prediction Algorithm-en_US.srt (2.4 KB)
• 14. Random Prediction Algorithm.mp4 (10.6 MB)
• 15. Zero Rule Algorithm-en_US.srt (4.4 KB)
• 15. Zero Rule Algorithm.mp4 (18.9 MB)
• 2. Scale Your Data Normalization-en_US.srt (3.7 KB)
• 2. Scale Your Data Normalization.mp4 (17.8 MB)
• 3. Scale Your Data Standardization-en_US.srt (3.7 KB)
• 3. Scale Your Data Standardization.mp4 (15.4 MB)
• 4. Algorithm Evaluation Methods-en_US.srt (1.5 KB)
• 4. Algorithm Evaluation Methods.mp4 (12.4 MB)
• 5. Train-Test Split-en_US.srt (3.8 KB)
• 5. Train-Test Split.mp4 (12.7 MB)
• 6. K-Fold Cross-Validation Defined-en_US.srt (2.7 KB)
• 6. K-Fold Cross-Validation Defined.mp4 (2.7 MB)
• 7. K-Fold Cross-Validation-en_US.srt (2.6 KB)
• 7. K-Fold Cross-Validation.mp4 (7.0 MB)
• 8. Choosing a Resampling Method-en_US.srt (1.9 KB)
• 8. Choosing a Resampling Method.mp4 (17.4 MB)
• 9. Evaluation Metrics-en_US.srt (2.0 KB)
• 9. Evaluation Metrics.mp4 (18.5 MB)
• Building Machine Learning Algorithms in Python - Baseline Algorithms.ipynb (2.9 KB)
• Building Machine Learning Algorithms in Python - Evaluation Metrics.ipynb (4.7 KB)
• Building Machine Learning Algorithms in Python - Loading Data.ipynb (5.0 KB)
• Building Machine Learning Algorithms in Python - Scaling Data with Normalization.ipynb (4.4 KB)
• Building Machine Learning Algorithms in Python - Scaling Data with Standardization.ipynb (4.7 KB)
3. Linear Algorithms
• 1. Algorithm Test Harness - Train-Test-Split-en_US.srt (5.6 KB)
• 1. Algorithm Test Harness - Train-Test-Split.mp4 (24.0 MB)
• 10. Demo Logistic Regression Make Predictions-en_US.srt (2.1 KB)
• 10. Demo Logistic Regression Make Predictions.mp4 (8.6 MB)
• 11. Demo Logistic Regression Estimating Coefficients-en_US.srt (3.4 KB)
• 11. Demo Logistic Regression Estimating Coefficients.mp4 (15.2 MB)
• 12. Demo Logistic Regression Diabetes Dataset-en_US.srt (2.6 KB)
• 12. Demo Logistic Regression Diabetes Dataset.mp4 (11.2 MB)
• 13. The Perceptron-en_US.srt (2.2 KB)
• 13. The Perceptron.mp4 (8.6 MB)
• 14. Demo The Perceptron Make Predictions-en_US.srt (3.1 KB)
• 14. Demo The Perceptron Make Predictions.mp4 (16.4 MB)
• 15. Demo The Perceptron Training Weights-en_US.srt (2.9 KB)
• 15. Demo The Perceptron Training Weights.mp4 (11.2 MB)
• 16. Demo The Perceptron Sonar Dataset-en_US.srt (2.5 KB)
• 16. Demo The Perceptron Sonar Dataset.mp4 (10.5 MB)
• 2. Algorithm Test Harness - K-Fold-en_US.srt (3.3 KB)
• 2. Algorithm Test Harness - K-Fold.mp4 (14.8 MB)
• 3. Simple Linear Regression-en_US.srt (3.2 KB)
• 3. Simple Linear Regression.mp4 (11.2 MB)
• 4. Simple Linear Regression Case Study-en_US.srt (4.0 KB)
• 4. Simple Linear Regression Case Study.mp4 (12.9 MB)
• 5. Simple Linear Regression Case Study Part 2-en_US.srt (3.2 KB)
• 5. Simple Linear Regression Case Study Part 2.mp4 (11.3 MB)
• 6. Multivariate Linear Regression Case Study-en_US.srt (2.4 KB)
• 6. Multivariate Linear Regression Case Study.mp4 (12.4 MB)
• 7. Demo Multivariate Linear Regression Case Study-en_US.srt (5.4 KB)
• 7. Demo Multivariate Linear Regression Case Study.mp4 (20.0 MB)
• 8. Demo Linear Regression on Wine Quality Dataset-en_US.srt (2.9 KB)
• 8. Demo Linear Regression on Wine Quality Dataset.mp4 (12.6 MB)
• 9. Logistic Regression Defined-en_US.srt (4.0 KB)
• 9. Logistic Regression Defined.mp4 (19.4 MB)
• Building Machine Learning Algorithms in Python - Algorithm Test Harness.ipynb (6.3 KB)
• Building Machine Learning Algorithms in Python - Simple Linear Regression.ipynb (8.9 KB)
• contrived-dataset.xlsx (36.7 KB)
• insurance.csv (0.5 KB)
4. Non-Linear Regression
• 1. Classification and Regression Trees-en_US.srt (3.4 KB)
• 1. Classification and Regression Trees.mp4 (8.5 MB)
• 10. Demo Naïve Bayes Separate by Class-en_US.srt (3.0 KB)
• 10. Demo Naïve Bayes Separate by Class.mp4 (9.3 MB)
• 11. Demo Naïve Bayes Summarize the Dataset-en_US.srt (3.9 KB)
• 11. Demo Naïve Bayes Summarize the Dataset.mp4 (15.2 MB)
• 12. Demo Naïve Bayes Summarize Data by Class-en_US.srt (2.0 KB)
• 12. Demo Naïve Bayes Summarize Data by Class.mp4 (7.7 MB)
• 2. Demo CART Creating the Gini Index-en_US.srt (3.6 KB)
• 2. Demo CART Creating the Gini Index.mp4 (13.9 MB)
• 3. Demo CART Creating the Splits-en_US.srt (1.8 KB)
• 3. Demo CART Creating the Splits.mp4 (5.4 MB)
• 4. Demo CART Evaluating the Splits-en_US.srt (2.8 KB)
• 4. Demo CART Evaluating the Splits.mp4 (12.4 MB)
• 5. CART Building the Tree-en_US.srt (3.1 KB)
• 5. CART Building the Tree.mp4 (5.9 MB)
• 6. Demo CART Recursive Splitting-en_US.srt (2.7 KB)
• 6. Demo CART Recursive Splitting.mp4 (9.6 MB)
• 7. Demo CART Assembling