As humans, we can quickly recognize images based on our past experiences. We have all seen trees, water, cars, and animals and we can easily differentiate a truck from an SUV and a chair from a couch. But, how do you teach a computer to do the same?
Machine Learning is a data science discipline that uses statistical algorithms to allow models to become more proficient at predicting results. Deep Learning is a subset of Machine Learning which uses a multiple-layer approach to solving complex, pattern matching problems.
This hands-on lab will help you to understand the concepts of Machine Learning and Deep Learning using Visual Recognition as a use case. You will use both coding and non-coding environments to build and train models that will differentiate between and categorize images.
Darrel is a Technical Evangelist with a background in business intelligence, data integration and data science. His experience also includes server administration, networking, programming, and engineering. He believes in unlocking the power of data and by utilizing systems and services, anything is possible. He strives to make individuals he interacts with the best they can be by educating, motivating, and teaming up to push the boundaries of what is possible with IBM. You may find him on Twitter, LinkedIn, or at various meetups.