Boosting your ROI with AutoML & Automatic Feature Engineering
As a data-driven business, you have to manage various forms of data from several source systems to generate better insights into your business. Breaking down the big data silos takes a lot of effort as well as time that somehow restricts you to think out of the box or focus more on other core components of your business. Using AutoML and Automatic Feature Engineering will help you efficiently solve numerous data science problems so that you can move your attention to other core processes and boost your ROI. To help you get a precise understanding of AutoML and Feature Engineering, we are here explaining them in brief:
MACHINE LEARNING/ARTIFICIAL INTELLIGENCE
Machine learning helps in building systems that can create great models by recognizing patterns from historical data so that they can operate in the real world without the need to construct any manual rules or codes to combat any possibility. The data scientists can use standard Machine Learning techniques to try different algorithms on historical data to find out the features that will affect the outcome of a decision like the adoption of a product, churn, and others.
The accuracy of the models can be maximized by cleansing the data, performing feature engineering, and tuning algorithms. Machine Learning build models having the highest accuracy to help in automating the repetitive tasks so that the productivity of the data scientist can be boosted, that in turn, boost the ROI of your business.
Now, if we talk about Artificial Intelligence, then it is a bigger term than Machine Learning. With loads of data coming on a daily basis, it becomes complex to make the best decisions out of them. With AI and ML, the process of data break down can be automated so that better business decisions can be made that will help the organizations to gain a competitive advantage and boost their ROI.
AUTOMATED FEATURE ENGINEERING
Automated Feature Engineering increases the productivity level of an organization by automating the process of extracting useful and relevant features from a given set of data tables with a framework that can be applied to every problem. It also filters out the time-independent data to prevent data leakage. The data spread across multiple tables is gathered into a single table having precise rows and columns that contain the features and observations in an accurate manner.
How AutoML and Feature Engineering help?
The main motive of AutoML & Feature Engineering is to provide you business. By helping you create the best and accurate models, the process of receiving and processing complex data can be automated so that the data scientist can focus on other major issues. As the data scientist can manage all the processes in an efficient manner, the projects can be finished before the deadlines.
With almost no effort, the data scientist can now create 100s of models automatically, and the AI will help them decide which model has the highest level of accuracy so that the same can be used to save the time and effort of data scientists in breaking down the complex data from several sources. With high accuracy models, the data scientist can boost their productivity and manage multiple projects within days and even hours. With the completion of projects before time, you can take new projects and increase your ROI at an exceptional rate. The models can be retained easily every time when a new data comes in, and in this way, they can always remain fresh in the production.
In the neck-to-neck competition, any decision can be a game-changer. Using the right tools, you can categorize the relevant data in the right place that will help you to develop better insights with no errors to make effective decisions and thus boosting your ROI.