Get ready for a journey inside machine learning, one that draws the connections between the mechanisms of a retail business and how you use machine learning to better understand the business.
This video starts by drawing a clear picture of the sales and revenue data points of a fictitious business and then maps them to the concepts of machine learning, in essence, showing you where to start to teach your system how to provide its own insights from your own data. You’ll meet a sample of data visualization, Brunel Visualization, to demonstrate a machine learning concept.
Once you’ve been introduced to the connecting points, the remainder of the video continues by demonstrating how a data scientist would use the IBM Machine Learning framework and Jupyter Notebooks to build a self-learning, predictive model that can drive the strategies on how to optimize your existing resources to achieve better outcomes – in this case, higher sales of a product line.
In the final portion of the demo, after the model has been tested, you observe the feedback loop and monitoring setup.
Resources for you
- Explore the application of machine and deep learning
- Machine learning is a necessity for cognitive IoT apps
- Learn more about using machine learning with Jupyter Notebooks | Explore Jupyter Notebooks
- Explore Watson machine learning on Bluemix | Try Bluemix for free
- Excellent tutorials and docs on machine learning at CloudDataServices Labs