1 00:00:00,381 --> 00:00:02,640 ‫Now, let's talk about Amazon Forecast. 2 00:00:02,640 --> 00:00:03,860 ‫And this is a very easy one 3 00:00:03,860 --> 00:00:06,080 ‫because it allows you to do forecasts. 4 00:00:06,080 --> 00:00:07,630 ‫So this is a fully managed services 5 00:00:07,630 --> 00:00:08,750 ‫that will use machine learning 6 00:00:08,750 --> 00:00:10,790 ‫to deliver a highly accurate forecast. 7 00:00:10,790 --> 00:00:13,280 ‫For example, you want to predict the future sales 8 00:00:13,280 --> 00:00:14,510 ‫of a raincoat. 9 00:00:14,510 --> 00:00:16,660 ‫The idea is that it's going to be 50% more accurate, 10 00:00:16,660 --> 00:00:18,450 ‫than looking at the data itself. 11 00:00:18,450 --> 00:00:21,280 ‫And you reduce forecasting time from months to hours 12 00:00:21,280 --> 00:00:22,990 ‫by using a managed service. 13 00:00:22,990 --> 00:00:24,330 ‫So the use cases can be multiple, 14 00:00:24,330 --> 00:00:25,380 ‫whenever you need a forecast. 15 00:00:25,380 --> 00:00:28,340 ‫For example, product demand planning, financial planning, 16 00:00:28,340 --> 00:00:30,110 ‫resource planning, and so on. 17 00:00:30,110 --> 00:00:31,090 ‫So how does it work? 18 00:00:31,090 --> 00:00:33,160 ‫Well, you take your historical time-series data, 19 00:00:33,160 --> 00:00:35,700 ‫for example, and you also add your product features, 20 00:00:35,700 --> 00:00:38,206 ‫prices, discounts, website traffic, store locations, 21 00:00:38,206 --> 00:00:40,010 ‫basically, any kind of data you can 22 00:00:40,010 --> 00:00:41,380 ‫to then enhance your model. 23 00:00:41,380 --> 00:00:43,790 ‫Then you upload this into Amazon S3. 24 00:00:43,790 --> 00:00:46,560 ‫You then start the Amazon Forecast service 25 00:00:46,560 --> 00:00:48,620 ‫which will create a forecasting model. 26 00:00:48,620 --> 00:00:50,570 ‫And you can use that forecasting model, for example, 27 00:00:50,570 --> 00:00:52,010 ‫to say that your future sales 28 00:00:52,010 --> 00:00:56,060 ‫of raincoats are going to be $500,000 next year. 29 00:00:56,060 --> 00:00:57,360 ‫And that's it, super simple. 30 00:00:57,360 --> 00:00:58,920 ‫Whenever you see forecasts at the exam, 31 00:00:58,920 --> 00:01:00,503 ‫think Amazon Forecast.