Predicting Website Traffic
The ability to accurately predict website traffic has significant implications for individuals and organizations, all of whom rely on fast, reliable website access for activities such as investing, ticket purchases, shopping, emergency information and notifications, and news access to name a few. Advances in technology, particularly mobile tech, have brought huge increases to website traffic across the board. Not properly anticipating web traffic on any given day - not to mention Black Friday! - can have extremely negative impacts to people and organizations resulting in lost revenue, damage to reputation, missed opportunities, or exposure to life-threatening situations.
The availability of large amounts of detailed web traffic data, along with advances in data science and computing power have made predicting website traffic much easier, accurate, and more reliable. This, in turn, has allowed system administrators and website managers the ability to better evaluate needs and plan system resources such as bandwidth and server space more efficiently. The end result is less website downtime and happier website visitors.
Automated machine learning (AutoML) is particularly well suited to the task of analyzing large website traffic datasets. Auger.AI’s AutoML tool greatly reduces the time spent selecting algorithms and tuning hyperparameters by automating the process and trying every available algorithm and hyperparameter combination. This process generates a leaderboard showing the best combinations from which an ensemble is created, combining the best attributes of the leading algorithms and hyperparameter options. Additionally, Auger employs a “warm start” process to algorithm/hyperparameter selection, generating more accurate results in less time.
All this means more accurate estimates of website traffic, allowing system admins to allocate resources more intelligently and efficiently, ultimately resulting in less website downtime and happier customers.
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