Machine Learning Data Science The Complete Visual Guide

1.9 GB | 13min 13s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
1 Course Structure & Outline.mp4 (15.59 MB)
4 Setting Expectations.mp4 (4.35 MB)
1 Intro to Machine Learning.mp4 (4.41 MB)
2 When is ML the right fit.mp4 (5.96 MB)
3 The Machine Learning Process.mp4 (5.42 MB)
4 The Machine Learning Landscape.mp4 (3.55 MB)
1 Part 1 QA & Data Profiling.mp4 (3.97 MB)
1 Introduction.mp4 (5.72 MB)
10 BEST PRACTICES Preliminary QA.mp4 (2.99 MB)
2 Why QA.mp4 (3.13 MB)
3 Variable Types.mp4 (5.86 MB)
4 Empty Values.mp4 (8.23 MB)
5 Range Calculations.mp4 (3.49 MB)
6 Count Calculations.mp4 (3.83 MB)
7 Left & Right Censored Data.mp4 (4.88 MB)
8 Table Structure.mp4 (5.33 MB)
9 CASE STUDY Preliminary QA.mp4 (152.6 MB)
1 Introduction.mp4 (4.51 MB)
10 CASE STUDY Normal Distribution.mp4 (46.08 MB)
11 Univariate Data Profiling.mp4 (3.43 MB)
12 Mode.mp4 (5.67 MB)
13 Mean.mp4 (3.9 MB)
14 Median.mp4 (2.66 MB)
15 Percentile.mp4 (3.01 MB)
16 Variance.mp4 (5.83 MB)
17 Standard Deviation.mp4 (2.79 MB)
18 Skewness.mp4 (2.82 MB)
19 BEST PRACTICES Univariate Profiling.mp4 (3.68 MB)
2 Categorical Variables.mp4 (3.58 MB)
3 Discretization.mp4 (3.75 MB)
4 Nominal vs Ordinal.mp4 (4.82 MB)
5 Categorical Distributions.mp4 (7.48 MB)
6 Numerical Variables.mp4 (3.81 MB)
7 Histograms & Kernel Densities.mp4 (10.63 MB)
8 CASE STUDY Histograms.mp4 (23.52 MB)
9 Normal Distribution.mp4 (5.11 MB)
1 Introduction.mp4 (17.04 MB)
10 Correlation.mp4 (7.01 MB)
11 Correlation vs Causation.mp4 (4.43 MB)
12 Visualizing Third Dimension.mp4 (5.44 MB)
13 CASE STUDY Correlation.mp4 (35.67 MB)
14 BEST PRACTICES Multivariate Profiling.mp4 (3.24 MB)
16 Looking Ahead to Part 2.mp4 (3.25 MB)
2 Categorical-Categorical.mp4 (7.35 MB)
3 CASE STUDY Heat Maps.mp4 (29.75 MB)
4 Categorical-Numerical.mp4 (5.3 MB)
5 Multivariate Kernel Densities.mp4 (6.09 MB)
6 Violin Plots.mp4 (3.44 MB)
7 Box Plots.mp4 (2.81 MB)
8 Limitations of Categorical Distributions.mp4 (5.23 MB)
9 Numerical-Numerical.mp4 (3.51 MB)
1 Part 2 Classification Modeling.mp4 (4.19 MB)
1 Supervised vs Unsupervised Learning.mp4 (8.88 MB)
2 Classification vs Regression.mp4 (3.84 MB)
3 RECAP Key Concepts.mp4 (6.97 MB)
4 Classification 101.mp4 (7.98 MB)
5 Classification Workflow.mp4 (5.89 MB)
6 Feature Engineering.mp4 (7.55 MB)
7 Data Splitting.mp4 (3.64 MB)
8 Overfitting.mp4 (7.68 MB)
1 Common Classification Models.mp4 (2.56 MB)
10 Decision Trees Entropy 101.mp4 (5.67 MB)
11 Entropy & Information Gain.mp4 (9.31 MB)
12 Decision Tree Examples.mp4 (10.45 MB)
13 Random Forests.mp4 (3.18 MB)
14 CASE STUDY Decision Trees.mp4 (38.98 MB)
15 Intro to Logistic Regression.mp4 (4.37 MB)
16 Logistic Regression Example.mp4 (5.08 MB)
17 False Positives vs False Negatives.mp4 (6.91 MB)
18 Logistic Regression Equation.mp4 (3.6 MB)
19 The Likelihood Function.mp4 (10 MB)
2 Intro to K-Nearest Neighbors (KNN).mp4 (2.3 MB)
20 Multivariate Logistic Regression.mp4 (5.85 MB)
21 CASE STUDY Logistic Regression.mp4 (39.25 MB)
22 Intro to Sentiment Analysis.mp4 (5.07 MB)
23 Cleaning Text Data.mp4 (4.16 MB)
24 Bag of Words Analysis.mp4 (9.26 MB)
25 CASE STUDY Sentiment Analysis.mp4 (38.65 MB)
3 KNN Examples.mp4 (8.44 MB)
4 CASE STUDY KNN.mp4 (78.03 MB)
5 Intro to Naïve Bayes.mp4 (3.28 MB)
6 Naïve Bayes Frequency Tables.mp4 (4.11 MB)
7 Naïve Bayes Conditional Probability.mp4 (11.1 MB)
8 CASE STUDY Naïve Bayes.mp4 (22.34 MB)
9 Intro to Decision Trees.mp4 (4.13 MB)
1 Intro to Selection & Tuning.mp4 (1.87 MB)
11 Looking ahead to Part 3.mp4 (1.32 MB)
2 Hyperparameters.mp4 (6.49 MB)
3 Imbalanced Classes.mp4 (7.06 MB)
4 Confusion Matrix.mp4 (4.68 MB)
5 Accuracy, Precision & Recall.mp4 (4.92 MB)
6 Multi-class Confusion Matrix.mp4 (4.66 MB)
7 Multi-class Scoring.mp4 (9.32 MB)
8 Model Selection.mp4 (3.77 MB)
9 Model Drift.mp4 (2.1 MB)
1 Part 3 Regression & Forecasting.mp4 (1.18 MB)
1 Supervised vs Unsupervised Learning.mp4 (4.43 MB)
2 RECAP Key Concepts.mp4 (5.63 MB)
3 Regression 101.mp4 (6.13 MB)
4 Feature Engineering for Regression.mp4 (6.32 MB)
5 Prediction vs Root-Cause Analysis.mp4 (2.41 MB)
1 Intro to Regression Modeling.mp4 (2.26 MB)
2 Linear Relationships.mp4 (11.88 MB)
3 Least Squared Error.mp4 (28.33 MB)
4 Univariate Linear Regression.mp4 (3.11 MB)
5 CASE STUDY Univariate Linear Regression.mp4 (29.08 MB)
6 Multiple Linear Regression.mp4 (19.34 MB)
7 Non-Linear Regression.mp4 (8.03 MB)
8 CASE STUDY Non-Linear Regression.mp4 (82.71 MB)
1 Intro to Model Diagnostics.mp4 (3.58 MB)
10 Variance Inflation Factor.mp4 (7.91 MB)
11 RECAP Sample Model Output.mp4 (10.09 MB)
2 Sample Model Output.mp4 (2.36 MB)
3 R-Squared.mp4 (10.44 MB)
4 Mean Error Metrics (MSE, MAE, MAPE).mp4 (12.79 MB)
5 Homoskedasticity.mp4 (5.37 MB)
6 Null Hypothesis.mp4 (2.47 MB)
7 F-Significance.mp4 (6.91 MB)
8 T-Values & P-Values.mp4 (9.22 MB)
9 Multicollinearity.mp4 (3.34 MB)
1 Intro to Forecasting.mp4 (4.72 MB)
10 CASE STUDY Smoothing.mp4 (24.12 MB)
11 Non-Linear Trends.mp4 (3.36 MB)
12 CASE STUDY Non-Linear Trend.mp4 (18.05 MB)
13 Intervention Analysis.mp4 (6.72 MB)
14 CASE STUDY Intervention Analysis.mp4 (58.65 MB)
16 Looking Ahead to Part 4.mp4 (1.64 MB)
2 Seasonality.mp4 (3.55 MB)
3 Auto Correlation Function.mp4 (5.05 MB)
4 CASE STUDY Seasonality with ACF.mp4 (16.95 MB)
5 One-Hot Encoding.mp4 (4.75 MB)
6 CASE STUDY Seasonality with One-Hot Encoding.mp4 (67.03 MB)
7 Linear Trending.mp4 (5.27 MB)
8 CASE STUDY Seasonality with Linear Trend.mp4 (59.67 MB)
9 Smoothing.mp4 (4.13 MB)
1 Part 4 Unsupervised Learning.mp4 (1.01 MB)
1 Supervised vs Unsupervised Learning.mp4 (4.29 MB)
2 Common Unsupervised Techniques.mp4 (3.21 MB)
3 Unsupervised ML Workflow.mp4 (4.05 MB)
4 RECAP Feature Engineering.mp4 (3 MB)
5 KEY TAKEAWAYS Intro to Unsupervised ML.mp4 (2.7 MB)
1 Introduction.mp4 (2.04 MB)
10 KEY TAKEAWAYS Clustering & Segmentation.mp4 (3.29 MB)
2 Clustering Basics.mp4 (4.44 MB)
3 Intro to K-Means.mp4 (16.34 MB)
4 WSS & Elbow Plots.mp4 (5.09 MB)
5 K-Means FAQs.mp4 (2.97 MB)
6 CASE STUDY K-Means.mp4 (91.95 MB)
7 Intro to Hierarchical Clustering.mp4 (6.25 MB)
8 Anatomy of a Dendrogram.mp4 (4.2 MB)
9 Hierarchical Clustering FAQs.mp4 (4.3 MB)
1 Introduction.mp4 (1.83 MB)
10 CASE STUDY Markov Chains.mp4 (15.97 MB)
11 KEY TAKEAWAYS Association Mining.mp4 (3.61 MB)
2 Association Mining Basics.mp4 (3.26 MB)
3 The Apriori Algorithm.mp4 (3.92 MB)
4 Basket Analysis Examples.mp4 (11.19 MB)
5 Minimum Support Thresholds.mp4 (3.06 MB)
6 Infrequent Itemsets.mp4 (8.2 MB)
7 Multiple Item Sets.mp4 (3.64 MB)
8 CASE STUDY Apriori.mp4 (48.04 MB)
9 Markov Chains.mp4 (11.52 MB)
1 Introduction.mp4 (3.24 MB)
2 Outlier Detection Basics.mp4 (4.49 MB)
3 Cross-Sectional Outliers.mp4 (4.87 MB)
4 Cross-Sectional Outlier Example.mp4 (8.08 MB)
5 CASE STUDY Cross-Sectional Outlier.mp4 (57.45 MB)
6 Time-Series Outliers.mp4 (3.92 MB)
7 Time-Series Outlier Example.mp4 (7.95 MB)
8 KEY TAKEAWAYS Outlier Detection.mp4 (2.55 MB)
1 Introduction.mp4 (987.21 KB)
2 Dimensionality Reduction Basics.mp4 (6.02 MB)
3 Principle Component Analysis.mp4 (3.46 MB)
4 PCA Example.mp4 (6.19 MB)
5 Interpreting Components.mp4 (6.43 MB)
6 Scree Plots.mp4 (5.91 MB)
7 Advanced Techniques.mp4 (2.22 MB)
8 KEY TAKEAWAYS Dimensionality Reduction.mp4 (2.67 MB)
1 Series Conclusion.mp4 (1.45 MB)]
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