Linear Regression Models E-Learning Kurs

Course Overview
Statistical Tools and Regression
Reasons to Use Regression
Regression Loss: Least Square Error
Capturing Variance in Regression
Prediction Using Regression
Introduction to Deep Learning
The Architecture of Neural Networks
Neurons: The Building Blocks of a Neural Network
Linear Regression Using a Single Neuron
Training a Neural Network
Gradient Descent Optimization
Exercise: Introduction to Linear Regression

Course Overview
Loading a Dataset
Splitting a Dataset for Training and Validation
Keras Installation
Training and Evaluating a Model
Building a Sequential Model
Training a Neural Network
Evaluating a Neural Network
Exercise: Building Simple Regression Models

Course Overview
Understanding Multiple Regression
Kitchen Sink Regression
Training and Evaluating the Model
Preparing Data for a Neural Network
Building a Neural Network
Evaluating the Neural Network
Finding Correlations in a Dataset
Introducing Parsimonious Regression
Applying Parsimonious Regression with Scikit Learn
Applying Parsimonious Regression with Keras
Exercise: Multiple Linear Regression

Course Overview
Introducing Logistic Regression
The Logistic Regression Curve
Logistic Regression and Classification
Logistic Regression vs. Linear Regression
Logistic Regression in Keras
Preparing Data for Logistic Regression
Classification using a Logistic Regression Model
Preparing Data for a Neural Network
Building and Evaluating the Keras Classifier
Exercise: An Introduction to Logistic Regression

Course Overview
Introducing Estimators
Preparing Data for a Linear Regressor Estimator
Training and Evaluating a Regressor Estimator
Preparing Data for a Linear Classifier Estimator
Training and Evaluating a Classifier Estimator
Exercise: Using TensorFlow Estimators