First of all, myth busted: the 1080 Ti can run minesweeper effortlessly. The machine did restart itself once for no obvious reasons after the proprietary GPU driver was installed. Back to the topic… Here is some R code for fitting a "wide and deep" classification model with Tensorflow and Tensorflow Estimators API. The model is fundamentally a direct combination of a linear model and a DNN model. The synthetic data has 1 million observations, 100 features (20 being useful) and is generated by my R package msaenet.
There is a great deal of speculation whether or not artificial intelligence and machine learning will take over the job market. Artificial intelligence will be able to automate jobs that many people thought could only be done by humans. However, there will be many new jobs created by artificial intelligence, machine learning and deep learning. In case you aren't aware machine learning is a subset of artificial intelligence and deep learning is a subset of machine learning. Companies are investing millions upon millions of dollars in artificial intelligence.
For those considering an autodidactic alternative, this is for you. You can't go deeply into every machine learning topic. There's too much to learn, and the field is advancing rapidly. Motivation is far more important than micro-optimizing a learning strategy for some long-term academic or career goal. If you're trying to force yourself forward, you'll slow down.
Previous Webinars – This webinar looks ahead to 2018 and developments we might see in the development and application of artificial intelligence and machine learning. With the pace of change so rapid in this area, predictions may be especially hard, but we will look at overall trends and pinpoint some areas of expected innovation. We will also examine the use cases we're seeing now and expect to see in 2018. And while it's very still very early days in the evolution of AI/ML but we will also look at areas of potential caution as the technology and market for it evolves.