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Commit b6d9e36

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update Ch 2 titles
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‎Lesson02/.ipynb_checkpoints/Chapter_2_Case_Study-checkpoint.ipynb

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{
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"cells": [
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Explore the target variable and conclude initial exploration"
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]
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},
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"mpl.rcParams['figure.dpi'] = 400 #high res figures"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Explore the target variable and conclude initial exploration"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Linear regression on synthetic data"
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"# Exercise X: Linear regression on synthetic data"
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"cell_type": "markdown",
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"# 3. Model performance metrics for binary classification\n",
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"# 3.1. Splitting the data: training and testing sets"
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"# Model performance metrics for binary classification\n",
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"## Splitting the data: training and testing sets"
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"cell_type": "markdown",
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"## 3.2. Classification accuracy"
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"## Classification accuracy"
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"attachments": {},
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"cell_type": "markdown",
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"source": [
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"## Exercise 2: Positives, negatives, and the confusion matrix"
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"# Exercise X: Calculating the True Positive Rate, False Positive Rate, and Confusion Matrix"
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"attachments": {},
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"cell_type": "markdown",
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"source": [
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"## Exercise 3: Predicted probabilities and the Receiver Operating Characteristic curve"
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"# Exercise X: Discovering Predicted Probabilities and the Creating Receiver Operating Characteristic (ROC) Curve"
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"attachments": {},
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"cell_type": "markdown",
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"source": [
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"# Activity"
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"# Activity: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve"
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‎Lesson02/Chapter_2_Case_Study.ipynb

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"cell_type": "markdown",
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"# Linear regression on synthetic data"
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"# Exercise X: Linear regression on synthetic data"
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"attachments": {},
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"metadata": {},
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"source": [
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"## Exercise 2: Positives, negatives, and the confusion matrix"
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"# Exercise X: Calculating the True Positive Rate, False Positive Rate, and Confusion Matrix"
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Exercise 3: Predicted probabilities and the Receiver Operating Characteristic curve"
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"# Exercise X: Discovering Predicted Probabilities and the Creating Receiver Operating Characteristic (ROC) Curve"
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"source": [
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"# Activity"
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"# Activity: Performing Logistic Regression with a New Feature and Creating a Precision-Recall Curve"
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