Starweaver

Statistics Module Slides - presentation

Focus and Objectives

READING: Intro to Machine Learning for Managers (Read Pages 1-12)

READING: Jeff Dean Rice Talk - State of Artificial Intelligence (Read entire document) (Dated but useful)

Module 1 - SLIDES - Part 1

Module 1 - SLIDES - Part 2

Module 1 - SLIDES - Part 3

Module 1 - SLIDES - Part 4

Module 1 - SLIDES - Part 5

Module 1 - SLIDES - Part 6

Module 1 - SLIDES - Part 7

Lesson 1: Introduction to Machine Learning

Lesson 1: Lab 1

Lesson 2-1: Lab-2a

Lesson 2-1: Pandas

Lesson 2-1: Exploring Pandas

Lesson 2-2: Lab-2b

Lesson 2-2: Lab 2c

Lesson 2-3: Visualization

Lesson 2-4: Lab-2d

Lesson 2-4: Visualization-Stats

Lesson 2-4: Lab 3a

Lesson 3-1: Sklearn

Lesson 3-2: Lab-3b

Lesson 3-2: Linear Regression

Lesson 3-3: Multivariate Linear Regression

Lesson 3-4: Logistic Regression (updated audio)

Module 2 - Focus and Objectives

READING: ISLR (Read Chapter 8 - Trees)

READING: ISLR (Read Chapter 9 - Support Vector Machine)

Lesson 1a: Classification (Support Vector Machines)

Lesson 1b: Classification (Naive Bayes)

Lesson 2-1: Lab1a and 1b

Focus and Objectives

READING: ISLR (Read Chapter 8 - Trees)

READING: ISLR (Read Chapter 9 - Support Vector Machine)

READING: ISLR (Read Chapter 10 - Unsupervised)

SLIDES - In pdf format (ALL SLIDES AVAILABLE HERE)

Module 3 - SLIDES - Part 1

Module 3 - SLIDES - Part 2

Module 3 - SLIDES - Part 3

Module 3 - SLIDES - Part 4

Module 3 - SLIDES - Part 5

Module 3 - SLIDES - Part 6

Lesson 1a: Classification (Support Vector Machines)

Lesson 1b: Classification (Naive Bayes)

Lesson 2-1: Lab1a and 1b

Lesson 2a: Decision Trees

Lesson 2b: Random Forests

Lesson 2-1: Lab-2a and 2b

Lesson 2-1: Lab-2c

Lesson 3a: Clustering

Lesson 3b: Principal Component Analysis

Lesson 2-1: Lab-3a and 3b

Lesson 3-1: Lab-3c (Principal Component Analysis)

Focus and Objectives

READING: Introduction to Deep Learning

READING: Introduction to Linear Algebra

READING: Introduction to Statistics

SLIDES - In pdf format (ALL SLIDES AVAILABLE HERE)

Module 4 - SLIDES - Part 1

Module 4 - SLIDES - Part 2

Module 4 - SLIDES - Part 3

Module 4 - SLIDES - Part 4

Module 4 - SLIDES - Part 5

Module 4 - SLIDES - Part 6

Module 4 - SLIDES - Part 7

Module 4 - SLIDES - Part 8

Module 4 - SLIDES - Part 9

Module 4 - SLIDES - Part 10

Lesson 1a: Deep Learning - Intro

Lesson 1a: Lab 1a - Tensorflow Playground

Lesson 1b: TensorFlow - Intro

Lesson 1b: Lab 1b - Tensorflow Sessions

Lesson 1c: TensorFlow- Low Level API

Lesson 2a: TensorFlow - Linear Models

Lesson 2a: Lab 2a and 2b

Lesson 2b: TensorFlow - High-Level API

Lesson 2b: Lab 2c and 2d

Lesson 3a: Lab 3a

Lesson 3a: Lab 3b and 3c

Lesson 3b: Lab 3d and 3e

Lesson 4: Multilayer Perceptron (MLP)

Focus and Objectives

READING: Place of Convolutional Neural Networks (CNN) and Deep Learning

READING: Parameter Sharing and CNN

READING: Understanding CNN

READING: A Brief History of CNNs in Image Segmentation

READING: CNN Architectures

SLIDES - In pdf format (ALL SLIDES AVAILABLE HERE)

Module 5 - SLIDES - Part 1

Lesson 1 - Convolutional Neural Networks

Lesson 2 - Convolutional Neural Networks, Extended

Lesson 3 - TensorBoard: Visualizing Learning