Automated Machine Learning – Not Just for Data Scientists
In today’s day and age, machine learning (ML) has become more in demand than ever. So much so, that it has surpassed the supply of highly skilled data scientists and ML engineers and experts. Automated Machine Learning (AutoML) has made it easier, faster, and cheaper to interpret data and make actionable predictions with little to no knowledge of data science or machine learning.Hiring personnel dedicated to machine learning and predictive data analytics can be costly, therefore ML solutions can be unattainable for organizations with limited IT budgets. But since this technology has been in such high demand, AutoML solutions have been developed to accomplish most of such tasks with ease.With AutoML, you can execute a machine learning task in just 30 minutes while running hundreds of algorithms simultaneously. In turn, this can save you time by being able to streamline the ML process and cut costs by not having to hire data scientists with a specific ML skill set.
How Auto-ML works
Because AutoML automatically finds and trains machine learning models, the models no longer need to be created by ML experts. AutoML algorithms work by analyzing your data and pick the best model to achieve whatever goal you have set and can streamline the process by eliminating the need for hyperparameter tuning and data augmentation.Even though AutoML fulfills the need for predictive analytics, if you want to produce higher-performing ML models, or produce a higher accuracy rate, you’ll need to have a fair amount of knowledge of data science. Even without this knowledge, Data-Core’s AutoML platform was created to be accessible and affordable to everyone regardless of expertise.The platform has a “build your own” approach and features the following:
- Allows users to control parameters, tuning, machine learning operations, and model assessments and allows hyper-personalized augmentation
- User-friendly and can be operated by those with limited statistical knowledge. Our platform does not require an in-depth understanding of data for data preparation and data modeling activities done inside the ML studio.
- Cloud-based platform that is integrated with leading standard AutoML providers in the industry like Azure, Google, and H2O.ai so you can compare data accuracy
- Eliminate tedious tasks, such as testing different ML approaches on the same data set to evaluate model performance
- Select the model of your choice and compare data accuracy using different models which will ultimately help you reduce risk factors in the prediction
- Models are deployed in containers and can be accessed via a simple API over the internet
- Models are updated automatically through MLOps after every validation cycle, which means you get the most recently trained model every time without any intervention
Make machine learning easier by automating it.Visit us at www.datacoreautomation.com/services/automl