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Премиум
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    Python for Business Analytics & Intelligence
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    Introduction
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    Setting up the Course Material
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    The Modern Day Business Analyst
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    Basic Statistics - Game Plan
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    Arithmetic Mean
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    CASE STUDY: Moneyball (Briefing)
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    Python - Directory, Libraries and Data
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    Python - Mean
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    EXERCISE: Python - Mean
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    Median and Mode
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    Python - Median
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    EXERCISE: Python - Median
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    Python - Mode
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    EXERCISE: Python - Mode
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    Correlation
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    Python - Correlation
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    EXERCISE: Python - Correlation
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    Standard Deviation
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    Python - Standard Deviation
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    EXERCISE: Python - Standard Deviation
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    CASE STUDY: Moneyball
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    Intermediary Statistics - Game Plan
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    Normal Distribution
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    CASE STUDY: Wine Quality (Briefing)
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    Python - Preparing Script and Loading Data
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    Python - Normal Distribution Visualization
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    EXERCISE: Python - Normal Distribution
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    P-Value
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    Shapiro-Wilks Test
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    Python - Shapiro-Wilks Test
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    EXERCISE: Python - Shapiro-Wilks
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    Standard Error of the Mean
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    Python - Standard Error
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    EXERCISE: Python - Standard Error
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    Z-Score
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    Confidence Interval
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    Python - Confidence Interval
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    EXERCISE: Python - Confidence Interval
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    T-test
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    CASE STUDY: Remote Work Predictions (Briefing)
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    Python - T-test
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    EXERCISE: Python - T-test
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    Chi-square test
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    Python - Chi-square test
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    EXERCISE: Python - Chi-square
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    Powerposing and p-hacking
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    Linear Regression - Game Plan
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    CASE STUDY: Diamonds (Briefing)
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    Linear Regression
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    Python - Preparing Script and Loading Data
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    Python - Isolate X and Y
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    Python - Adding Constant
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    Linear Regression Output
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    Python - Linear Regression Model and Summary
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    Python - Plotting Regression
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    Dummy Variable Trap
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    Python - Dummy Variable
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    EXERCISE: Python - Linear Regression
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    Multilinear Regression - Game Plan
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    The Concept of Multilinear Regression
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    CASE STUDY: Professors' Salary (Briefing)
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    Python - Preparing Script and Loading Data
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    Python - Summary Statistics
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    Outliers
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    Python - Plotting Continuous Variables
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    Python - Correlation Matrix
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    Python - Categorical Variables
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    Python - For Loop
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    Python - Creating Dummy Variables
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    Python - Isolate X and Y
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    Python - Adding Constant
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    Under and Over Fitting
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    Training and Test Set
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    Python - Train and Test Split
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    Python - Multilinear Regression
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    Accuracy KPIs (Key Performance Indicators)
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    Python - Model Predictions
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    Python - Accuracy Assessment
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    Logistic Regression - Game Plan
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    CASE STUDY: Spam Emails (Briefing)
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    Logistic Regression
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    Python - Preparing Script and Loading Data
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    Python - Summary Statistics
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    Python - Histogram and Outlier Removal
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    Python - Correlation Matrix
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    Python - Transforming Dependent Variable
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    Python - Prepare X and Y
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    Python - Training and Test Set
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    How to Read Logistic Regression Coefficients
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    Python - Logistic Regression
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    Python - Function to Read Coefficients
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    Python - Predictions
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    Confusion Matrix
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    Python - Confusion Matrix
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    Python - Manual Accuracy Assessment
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    Python - Classification Report
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    Why Econometrics and Causal Inference
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    Google Causal Impact - Game Plan
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    Time Series Data
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    CASE STUDY: Bitcoin Pricing (Briefing)
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    Difference-in-Differences Framework
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    Causal Impact Step-by-Step
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    Python - Installing and Importing Libraries
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    Python - Defining Dates
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    Python - Bitcoin Price loading
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    Assumptions
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    Python - Load Control Groups
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    Python - Preparing DataFrame
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    Python - Preparing for Correlation Matrix
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    Correlation Recap and Stationarity
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    Python - Stationarity
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    Python - Correlation
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    Python - Google Causal Impact Setup
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    Python - Google Causal Impact
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    Interpretation of Results
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    Python - Impact Results
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    Matching - Game Plan
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    Matching
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    CASE STUDY: Catholic Schools & Standardized Tests (Briefing)
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    Python - Directory and Libraries
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    Python - Loading Data
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    Unconfoundedness
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    Python - Comparing Means
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    Python - T-Test
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    Python - T-Test Loop
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    Python - Chi-square Test
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    Python - Chi-square Loop
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    Python - Other Variables
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    The Curse of Dimensionality
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    Python - Race Variable Transformation
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    Python - Education Variables
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    Python - Cleaning and Preparing Dataset
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    Common Support Region
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    Python - Logistic Regression and Debugging
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    Python - Preparing for Common Support Region
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    Python - Common Support Region Visualization
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    Python - Matching
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    Robustness Checks
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    Python - Robustness Check - Repeated experiments
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    Python - Outcome Visualization
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    Python - Robustness Check - Removing 1 confounder
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    My Experience with Matching
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    RFM - Game Plan
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    Value Based Segmentation
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    RFM Model
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    CASE STUDY: Online Shopping (Briefing)
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    Python - Directory and Libraries
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    Python - Loading Data
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    Python - Creating Sales Variable
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    Python - Date Variable
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    Python - Customer Level Aggregation
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    Python - Monetary Variable
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    Python - Tidying up Dataframe
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    Python - Quartiles
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    Python - RFM Score
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    Python - RFM Function
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    Python - Applying RFM Function
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    Python - Results Summary
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    Gaussian Mixture - Game Plan
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    Clustering
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    Gaussian Mixture Model
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    CASE STUDY: Credit Cards #1 (Briefing)
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    Python - Directory and Data
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    Python - Load Data
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    Python - Transform Character variables
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    AIC and BIC
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    Python - Optimal Number of Clusters
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    Python - Gaussian Mixture Model
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    Python - Cluster Prediction and Assignment
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    Python - Interpretation
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions
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    My Experience with Segmentation
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    Random Forest - Game Plan
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    Ensemble Learning and Random Forest
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    How Decision Trees Work
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    CASE STUDY: Credit Cards #2 (Briefing)
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    Python - Directory and Libraries
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    Python - Loading Data
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    Python - Transform Object into Numerical Variables
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    Python - Summary Statistics
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    Random Forest Quirks
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    Python - Isolate X and Y
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    Python - Training and Test Set
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    Python - Random Forest Model
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    Python - Predictions
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    Python - Classification Report and F1 score
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    Python - Feature Importance
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    Parameter Tuning
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    Python - Parameter Grid
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    Python - Parameter Tuning
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions (Part 1)
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    CHALLENGE: Solutions (Part 2)
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    Facebook Prophet - Game Plan
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    Structural Time Series
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    Facebook Prophet
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    CASE STUDY: Wikipedia (Briefing)
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    Python - Directory and Libraries
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    Python - Loading Data
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    Python - Transforming Date Variable
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    Python - Renaming Variables
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    Dynamic Holidays
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    Python - Easter Holidays
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    Python - Black Friday
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    Python - Combining Events and Preparing Dataframe
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    Training and Test Set
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    Python - Training and Test Set
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    Facebook Prophet Parameters
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    Additive vs. Multiplicative Seasonality
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    Facebook Prophet Model
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    Python - Regressor Coefficients
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    Python - Future Dataframe
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    Python - Forecasting
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    Python - Accuracy Assessment
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    Python - Visualization
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    Cross-validation
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    Python - Cross-validation
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    Parameters to tune
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    Python - Parameter Grid
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    Python - Parameter Tuning
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    CHALLENGE: Introduction
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    CHALLENGE: Solutions (Part 1)
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    CHALLENGE: Solutions (Part 2)
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    CHALLENGE: Solutions (Part 3)
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    Forecasting at Uber
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    Thank You!