Ople uses AI to accelerate data science, continuously optimizing algorithms and outcomes to deliver results sooner. This means more accurate forecasting, earlier decision making, and reduced risk-taking. Ople’s speed and accuracy come from its unequaled deep learning approach BASS, which uses behavioral assimilation to learn from each model and dataset. In fact, BASS enables Ople to automate many of the tedious processes that encumber Data Scientists, increasing Data Science team’s ability to formulate and create AI models by as much as 10X.
The first step is to organize and assess your training data set. Unlike other AI and analytics platforms, with Ople, you do not have to cleanse your data until it is pristine. In reality, your training data set should be as similar as possible to your production dataset. So, if your production dataset is likely to be a bit dirty, then your training data set should also be “a bit dirty,” resembling your production dataset to the greatest extent possible.
Files are expected to be CSV with suggested column prefixes:
i: index column, excluded from training
n: numeric feature column
c: categorical feature column
t: target column, these are the columns you are trying to predict
‘id, num1, num2, n_count, cat1, cat2, c_employed, target’
After uploading your data set, Ople processes the data and uses it to train the AI engine, map and generate preliminary results to assure consistent data quality.
From the initial results, you can validate that the automated results are meeting or exceeding your human expectations of accuracy.
According to your rules and criteria, Ople quickly generates a custom AI model and automatically compares the results to those of industry leading models, learning from each of these models.
No longer will you wait weeks and discover that a model is not optimal. Ople generates an optimized AI model specifically for your data.
Putting Final Model Into Production
With the validated data, the Ople AI optimized model can be quickly deployed with the touch of a button! Ople will run your data through the customized model for anywhere between a few minutes and a few days, depending on the complexity of the model and the quality of the data.
No longer will you wait many weeks to get results. While Ople automates and accelerates the process, the data science team should now have the confidence and time pursue their intuition, creating even more models to tackle additional business challenges.