Section 1 : Introduction
Lecture 1 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 2 Course Introduction What to Expect copy 00:06:10 Duration
Lecture 3 Get the Course Materials 00:01:42 Duration

Section 2 : Data Engineering
Lecture 1 Section Intro Data Engineering 00:01:05 Duration
Lecture 2 Amazon S3 - Overview 00:05:04 Duration
Lecture 3 Amazon S3 - Storage Tiers & Lifecycle Rules 00:04:30 Duration
Lecture 4 Amazon S3 Security 00:08:06 Duration
Lecture 5 Kinesis Data Streams & Kinesis Data Firehose 00:08:38 Duration
Lecture 6 Lab 1 00:06:04 Duration
Lecture 7 Kinesis Data Analytics 00:04:25 Duration
Lecture 8 Lab 1 00:07:23 Duration
Lecture 9 Kinesis Video Streams 00:02:55 Duration
Lecture 10 Kinesis ML Summary 00:01:12 Duration
Lecture 11 Glue Data Catalog & Crawlers 00:02:32 Duration
Lecture 12 Lab 1 00:04:23 Duration
Lecture 13 Glue ETL 00:02:10 Duration
Lecture 14 Lab 1 00:06:21 Duration
Lecture 15 Lab 1 00:01:27 Duration
Lecture 16 Lab 1 - Cleanup 00:01:32 Duration
Lecture 17 AWS Data Stores in Machine Learning 00:03:10 Duration
Lecture 18 AWS Data Pipelines 00:02:39 Duration
Lecture 19 AWS Batch 00:01:52 Duration
Lecture 20 AWS Step Functions 00:02:44 Duration
Lecture 21 Full Data Engineering Pipelines 00:05:09 Duration
Lecture 22 Data Engineering Summary

Section 3 : Exploratory Data Analysis
Lecture 1 Section Intro Data Analysis 00:01:13 Duration
Lecture 2 Python in Data Science and Machine Learning 00:12:08 Duration
Lecture 3 Example Preparing Data for Machine Learning in a Jupyter Notebook 00:10:21 Duration
Lecture 4 Types of Data 00:04:31 Duration
Lecture 5 Data Distributions 00:06:06 Duration
Lecture 6 Time Series Trends and Seasonality 00:03:57 Duration
Lecture 7 Introduction to Amazon Athena 00:05:07 Duration
Lecture 8 Overview of Amazon Quicksight 00:05:59 Duration
Lecture 9 Types of Visualizations, and When to Use Them
Lecture 10 Elastic MapReduce (EMR) and Hadoop Overview 00:07:15 Duration
Lecture 11 Apache Spark on EMR 00:09:59 Duration
Lecture 12 EMR Notebooks, Security, and Instance Types 00:04:10 Duration
Lecture 13 Feature Engineering and the Curse of Dimensionality 00:06:34 Duration
Lecture 14 Imputing Missing Data
Lecture 15 Dealing with Unbalanced Data 00:05:35 Duration
Lecture 16 Handling Outliers 00:08:30 Duration
Lecture 17 Binning, Transforming, Encoding, Scaling, and Shuffling 00:07:59 Duration
Lecture 18 Amazon SageMaker Ground Truth and Label Generation 00:04:28 Duration
Lecture 19 Lab Preparing Data for TF-IDF with Spark and EMR, Part 1 00:06:18 Duration
Lecture 20 Lab Preparing Data for TF-IDF with Spark and EMR, Part 2 00:09:46 Duration
Lecture 21 Lab Preparing Data for TF-IDF with Spark and EMR, Part 3 00:13:29 Duration

Section 4 : Modeling
Lecture 1 Section Intro Modeling 00:01:48 Duration
Lecture 2 Introduction to Deep Learning 00:09:23 Duration
Lecture 3 Activation Functions 00:10:50 Duration
Lecture 4 Convolutional Neural Networks 00:12:07 Duration
Lecture 5 Recurrent Neural Networks 00:10:49 Duration
Lecture 6 Deep Learning on EC2 and EMR 00:01:32 Duration
Lecture 7 Tuning Neural Networks 00:04:48 Duration
Lecture 8 Regularization Techniques for Neural Networks (Dropout, Early Stopping)
Lecture 9 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 10 L1 and L2 Regularization 00:03:04 Duration
Lecture 11 The Confusion Matrix 00:05:30 Duration
Lecture 12 Precision, Recall, F1, AUC, and more 00:06:59 Duration
Lecture 13 Ensemble Methods Bagging and Boosting 00:03:43 Duration
Lecture 14 Introducing Amazon SageMaker 00:08:07 Duration
Lecture 15 Linear Learner in SageMaker 00:04:59 Duration
Lecture 16 XGBoost in SageMaker 00:03:00 Duration
Lecture 17 Seq2Seq in SageMaker 00:04:47 Duration
Lecture 18 DeepAR in SageMaker
Lecture 19 BlazingText in SageMaker 00:04:56 Duration
Lecture 20 Object2Vec in SageMaker 00:04:44 Duration
Lecture 21 Object Detection in SageMaker 00:04:02 Duration
Lecture 22 Image Classification in SageMaker 00:04:08 Duration
Lecture 23 Semantic Segmentation in SageMaker 00:03:48 Duration
Lecture 24 Random Cut Forest in SageMaker 00:03:01 Duration
Lecture 25 Neural Topic Model in SageMaker 00:03:25 Duration
Lecture 26 Latent Dirichlet Allocation (LDA) in SageMaker 00:03:10 Duration
Lecture 27 K-Nearest-Neighbors (KNN) in SageMaker 00:03:00 Duration
Lecture 28 K-Means Clustering in SageMaker 00:05:00 Duration
Lecture 29 Principal Component Analysis (PCA) in SageMaker
Lecture 30 Factorization Machines in SageMaker 00:04:12 Duration
Lecture 31 IP Insights in SageMaker 00:02:58 Duration
Lecture 32 Reinforcement Learning in SageMaker 00:12:23 Duration
Lecture 33 Automatic Model Tuning 00:05:55 Duration
Lecture 34 Apache Spark with SageMaker 00:03:17 Duration
Lecture 35 SageMaker Studio, and new SageMaker features for 2020 00:06:06 Duration
Lecture 36 Amazon Comprehend 00:05:49 Duration
Lecture 37 Amazon Translate 00:01:55 Duration
Lecture 38 Amazon Transcribe 00:04:17 Duration
Lecture 39 Amazon Polly 00:05:38 Duration
Lecture 40 Amazon Rekognition 00:07:45 Duration
Lecture 41 Amazon Forecast 00:01:45 Duration
Lecture 42 Amazon Lex 00:03:07 Duration
Lecture 43 The Best of the Rest Other High-Level AWS Machine Learning Services 00:02:50 Duration
Lecture 44 New ML Services for 2020 00:06:19 Duration
Lecture 45 Putting them All Together 00:02:08 Duration
Lecture 46 Lab Tuning a Convolutional Neural Network on EC2, Part 1 00:08:59 Duration
Lecture 47 Lab Tuning a Convolutional Neural Network on EC2, Part 2 00:09:06 Duration
Lecture 48 Lab Tuning a Convolutional Neural Network on EC2, Part 3 00:06:29 Duration

Section 5 : ML Implementation and Operations
Lecture 1 Section Intro Machine Learning Implementation and Operations 00:01:10 Duration
Lecture 2 SageMaker's Inner Details and Production Variants 00:10:56 Duration
Lecture 3 SageMaker On the Edge SageMaker Neo and IoT Greengrass 00:04:18 Duration
Lecture 4 SageMaker Security Encryption at Rest and In Transit 00:04:31 Duration
Lecture 5 SageMaker Security VPC's, IAM, Logging, and Monitoring 00:04:03 Duration
Lecture 6 SageMaker Resource Management Instance Types and Spot Training 00:03:35 Duration
Lecture 7 SageMaker Resource Management Elastic Inference, Automatic Scaling, AZ's 00:04:34 Duration
Lecture 8 SageMaker Inference Pipelines 00:01:39 Duration
Lecture 9 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 1 00:05:21 Duration
Lecture 10 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 2 00:10:33 Duration
Lecture 11 Lab Tuning, Deploying, and Predicting with Tensorflow on SageMaker - Part 3 00:12:21 Duration

Section 6 : Wrapping Up
Lecture 1 Section Intro Wrapping Up 00:00:24 Duration
Lecture 2 More Preparation Resources 00:05:53 Duration
Lecture 3 Test-Taking Strategies, and What to Expect 00:10:04 Duration
Lecture 4 You Made It! 00:00:46 Duration
Lecture 5 Save 50% on your AWS Exam Cost! 00:01:42 Duration
Lecture 6 Get an Extra 30 Minutes on your AWS Exam - Non Native English Speakers only 00:01:09 Duration