We're excited to announce that you can now automatically monitor the accuracy of your Amazon Forecast predictors over time. As new data is provided, Forecast automatically computes predictor accuracy metrics, providing you with more information to decide whether to keep using, retrain, or create new predictors. Monitoring predictor quality and identifying deterioration in accuracy over time is important to achieving business goals. However, the processes required to continuously monitor predictor accuracy metrics can be time-consuming to set up and challenging to manage: forecasts have to be evaluated, and updated accuracy metrics have to be computed. In addition, metrics have to be stored and charted to understand trends and make decisions about keeping, retraining, or recreating predictors.

What is Amazon Web Services? Amazon Web Services or AWS is world's broadly adopted cloud platform . AWS provides with a number of useful cloud computing services that are very much reliable, scalable and cost efficient as they say. AWS provides services like storage, networking, remote computing, servers, email, mobile development and security . So now coming to Amazon machine learning, frankly means leveraging ML algorithms on cloud platforms like AWS .

You might use traditional methods to forecast future business outcomes, but these traditional methods are often not flexible enough to account for varying factors, such as weather or promotions, outside of the traditional time series data considered. With the advancement of machine learning (ML) and the elasticity that the AWS Cloud brings, you can now enjoy more accurate forecasts that influence business decisions. You will learn how to interpret and format your data according to what Amazon Forecast needs based on your business questions. This post shows you how to prepare your data to optimally use with Amazon Forecast. Amazon Forecast is a fully managed service that allows you to forecast your time series data with high accuracy. It uses ML to analyze complex relationships in historical data and doesn't require any prior ML experience.

Amazon Forecast is a fully managed service that is based on the same technology used for forecasting at Amazon.com. Forecast uses machine learning (ML) to combine time series data with additional variables to build highly accurate forecasts. Forecast requires no ML experience to get started. You only need to provide historical data and any additional data that may impact forecasts. Customers are turning towards using a Software as service (SaaS) model for delivery of multi-tenant solutions.

We're excited to announce that you can now measure the accuracy of your forecasting model to optimize the trade-offs between under-forecasting and over-forecasting costs, giving you flexibility in experimentation. Costs associated with under-forecasting and over-forecasting differ. Generally, over-forecasting leads to high inventory carrying costs and waste, whereas under-forecasting leads to stock-outs, unmet demand, and missed revenue opportunities. Amazon Forecast allows you to optimize these costs for your business objective by providing an average forecast as well as a distribution of forecasts that captures variability of demand from a minimum to maximum value. With this launch, Forecast now provides accuracy metrics for multiple distribution points when training a model, allowing you to quickly optimize for under-forecasting and over-forecasting without the need to manually calculate metrics.

Machine Learning and Artificial Intelligence (ML/AI) is being adopted by businesses across all industries at an ever-increasing rate. An organization's ability to leverage ML/AI technology depends on numerous factors. For starters, wrangling all of your data is no small feat. Recruiting and retaining talent with the necessary domain knowledge to put your data to work is also a big challenge. Combine all of that with the specialized hardware and systems required to develop and train models, and the endeavor quickly becomes unapproachable for many businesses that don't have a tech giant's resources and budget.

Amazon Web Services has announced the general availability of Amazon Forecast, a fully managed service that uses machine learning to deliver highly accurate forecasts based on the same technology that powers Amazon.com. Amazon uses forecasting to make sure that the right product is in the right place at the right time by predicting demand for hundreds of millions of products every day. Amazon Forecast uses this same technology to build precise forecasts for virtually any business condition, including product demand and sales, infrastructure requirements, energy needs, and staffing levels – with predictions that are up to 50% more accurate than traditional methods. Amazon Forecast is easy to use and requires no machine learning experience. The service automatically provisions the necessary infrastructure, processes data, and builds custom, private machine learning models that are hosted on AWS and ready to make predictions.

In a recent blog post, Amazon announced the general availability (GA) of Amazon Forecast, a fully managed, time series data forecasting service. Amazon Forecast uses deep learning from multiple datasets and algorithms to make predictions in the areas of product demand, travel demand, financial planning, SAP and Oracle supply chain planning and cloud computing usage. While Amazon Forecasts leverages machine learning within its service, users of the service do not require machine learning expertise. Amazon Forecast was originally announced at re:Invent 2018 and is now available for production use via the AWS Console, AWS Command Line Interface (CLI) and AWS SDKs. The service was conceived as a result of customer demand, since Amazon has extensive experience in forecasting for their own lines of business.

Amazon uses forecasting to make sure that the right product is in the right place at the right time by predicting demand for hundreds of millions of products every day. Amazon Forecast uses this same technology to build precise forecasts for virtually any business condition, including product demand and sales, infrastructure requirements, energy needs, and staffing levels – with predictions that are up to 50% more accurate than traditional methods. Amazon Forecast is easy to use and requires no machine learning experience. The service automatically provisions the necessary infrastructure, processes data, and builds custom, private machine learning models that are hosted on AWS and ready to make predictions. To get started with Amazon Forecast, visit https://aws.amazon.com/forecast/.

The ability to forecast events at scale, given a set of variables, is something most companies would find useful. So Amazon is aiming to make prediction more accessible with a fully managed service called Forecast that uses AI and machine learning to deliver highly accurate forecasts. As Amazon explained in a press release, Forecast -- which is based on the same technology the Seattle company uses to anticipate demand for hundreds of millions of products every day -- can be used to build precise forecasts for virtually any business condition, including product demand and sales, infrastructure requirements, energy needs, and staffing levels. It automatically provisions the necessary cloud infrastructure and processes data, building custom AI models hosted on AWS without requiring an ounce of machine learning experience on the part of developers. Amazon says the API or a console allows the average person to build custom machine learning models in less than five clicks and achieve accuracy levels that would normally take months in as little as a few hours.