Section 1 : Module 1 Introduction to Machine Learning

 		Lecture 1 Introduction to Machine Learning 53:11
Lecture 2 Lesson 1 Lab 1 8:23
Lecture 3 Lesson 2-1 Lab-2a 1:53
Lecture 4 Lesson 2-1 Pandas 35:26
Lecture 5 Lesson 2-1 Exploring Pandas
Lecture 6 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM Pdf
Lecture 7 Lesson 2-2 Lab 2c 1:49
Lecture 8 Lesson 2-3 Visualization 18:42
Lecture 9 Lesson 2-4 Lab-2d 1:30
Lecture 10 Lesson 2-4 Visualization-Stats 13:25
Lecture 11 Lesson 2-4 Lab 3a 3:30
Lecture 12 Lesson 3-1 Sklearn 29:56
Lecture 13 Lesson 3-2 Lab-3b 1:38
Lecture 14 Lesson 3-2 Linear Regression 12:50
Lecture 15 Lesson 3-3 Multivariate Linear Regression 7:16
Lecture 16 Lesson 3-4 Logistic Regression (updated audio) 22:22

Section 2 : Module 2 Exploring and Using Data Sets

 		Lecture 17 Lesson 1a Classification (Support Vector Machines) 21:20
Lecture 18 Lesson 1b Classification (Naive Bayes)
Lecture 19 Lesson 2-1 Lab1a and 1b 2:38
Lecture 20 Lesson 1a Classification (Support Vector Machines) 2:38
Lecture 21 dsml-seg-20-Decision_Trees 27:2
Lecture 22 dsml-seg-21-RandomForests 13:21
Lecture 23 dsml-seg-22-Lab2a_2b 2:59
Lecture 24 dsml-seg-23-Lab2c 2:43
Lecture 25 dsml-seg-24-clustering 26:37
Lecture 26 dsml-seg-25-pca 20:59
Lecture 27 dsml-seg-26-lab_3a_3b 3:52
Lecture 28 dsml-seg-27-lab_3c 4:21

Section 3 : Module 3 Review of Machine Learning Algorithms

 		Lecture 29 dsml-seg-28-deep-learning-introduction
Lecture 30 dsml-seg-29-Lab_1a 3:20
Lecture 31 dsml-seg-30-tensorflow-introduction 9:17
Lecture 32 dsml-seg-31-lab_1b 1:24
Lecture 33 dsml-seg-32-tensorflow-Low-Level 14:14
Lecture 34 dsml-seg-33-tensorfiow-Linear-Models 14:14
Lecture 35 dsml-seg-33-tensorfiow-Linear-Models
Lecture 36 dsml-seg-34-lab_2a_2b 2:23
Lecture 37 dsml-seg-35-tensorflow-High-Level-API 14:53
Lecture 38 dsml-seg-36-Lab_2c_2d 2:16
Lecture 39 dsml-seg-37-lab_3a 1:52
Lecture 40 dsml-seg-38-lab_3b_3c 2:57
Lecture 41 dsml-seg-39-lab_3d_3e 4:32
Lecture 42 dsml-seg-40-multilayer-perceptron-mlp

Section 4 : Module 4 Machine Learning with Scikit

 		Lecture 43 dsml-seg-41-convolutional-neural-network 33:31
Lecture 44 dsml-seg-42-convolutional-neural-network-extended 20:46
Lecture 45 dsml-seg-43-tensorboard 10:4

Section 5 : Module 5 Deep Learning with Keras and TensorFlow

 		Lecture 46 dsml-seg-44-transfer-learning 15:52
Lecture 47 dsml-seg-45-recurrent-neural-network 29:31
Lecture 48 dsml-seg-46-long-short-term-memory 34:51

Section 6 : Module 7 Building a Machine Learning Pipeline

 		Lecture 49 dsml-seg-47-scaling-machine-learning-distributed-tensorflow 31:34
Lecture 50 dsml-seg-48-feature-engineering 25:19
Lecture 51 dsml-seg-49-pipeline-examples 3:48