Machine Learning and AI Foundations : Predictive Modeling Strategy at Scale

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In this video we are going to see the basics of Machine Learning and AI . These are the fundamentals of Machine Learning and AI and essential trainings. we will see more and more in upcoming videos.

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Where There is a Will There is a Way 💘
//Chapters and time splits

00:00:00-00:01:38 Scaling machine learning initiatives
00:01:39-00:03:26 Defining terms
00:03:27-00:05:26 Data and supervised machine learning
00:05:27-00:08:56 The nine big data bottlenecks
00:08:57-00:11:53 The stages of predictive analytics data
00:11:54-00:13:32 Why you might have too little data
00:13:33-00:15:44 How much data do I need?
00:15:45-00:17:40 Balancing
00:17:41-00:21:12 Assessing data
00:21:13-00:23:13 Selecting: Data that should be left out
00:23:14-00:27:15 Seasonality and time alignment
00:27:16-00:30:10 Data and the data scientist
00:30:11-00:32:12 Aggregate and restructure
00:32:13-00:34:13 Dummy coding
00:34:14-00:37:04 Feature engineering
00:37:05-00:39:41 Understanding the modeling process
00:39:42-00:41:40 Slow algorithms: Brute force
00:41:41-00:43:10 Slow algorithms: More calculations
00:43:11-00:45:34 Slow algorithms: More models
00:45:35-00:48:10 How to sample properly
00:48:11-00:51:47 Modeling with missing data
00:51:48-00:54:37 Scoring traditional ML models
00:54:38-00:57:27 Scoring a black box model
00:57:28-00:59:16 Scoring an ensemble
00:59:17-01:03:55 Batch vs real-time scoring
01:03:56-01:06:54 Data prep and scoring
01:06:55-01:08:42 Combining batch and real-time scoring
01:08:43-01:12:48 What is model monitoring?
01:12:49-01:16:42 How often should you rebuild?
01:16:43-01:17:43 Next steps

Видео Machine Learning and AI Foundations : Predictive Modeling Strategy at Scale канала miss google