The new age of analytics is driven by neural networks, algorithms, and machine learning empowered by collaboration and open source frameworks. When implementing a machine learning program at your organization, there are many questions to consider. What do you do? How do you succeed? Where do you learn from? Whom do you follow? Is it DevOps transformation in the enterprise? Do you need programmers and coding experts to drive analytics? In addition, there are several algorithms to learn and implement in the ecosystem, where the answers are asked prior to the questions. Attend this session to learn the keys to implementing a successful machine learning program.
You Will Learn
- Successful machine learning implementation: A business case
- Selecting and implementing machine learning algorithms: A roadmap framework
- Case study: Implementing TensorFlow neural networks
- Pitfalls, risks, and opportunities
- Analytics, DevOps, and data professionals