ML Conference 2017: Bringing machine learning innovation to the world
Machine Learning is the next big thing. Are you ready? The ML Conference 2017 program is now live! Here’s a sneak peek of some of the awesome sessions, workshops, and keynotes that are already scheduled. Book your tickets now and save up to €180!
Are you looking to enhance your business with Machine Learning? Then ML Conference is for you. It gives you a comprehensive insight into the principles of Machine Learning and introduces to the world of ML tools, programming languages and technologies. Experienced ML speakers from a solid industry background show you how to create real value from Artificial Intelligence using the latest technologies such as Tensorflow, Deep Learning toolkits, Chatbots and many more.
The ML conference boasts three separate tracks: Machine Learning Principles; Machine Learning Tools, APIs, and Solutions; and Programming and Data-Driven Solutions.
Here’s what the schedule looks like so far:
4th December — Power workshops
- 2 hands-on workshops by international trainers
- Full day of live demos and case studies of real-world implementations
- Machine Learning in practice addressing current challenges
- Buffet of food and refreshments during the day is included
5th – 6th December — Main conference
- 20+Workshops, sessions and keynotes
- 30+International speakers and experts
- ML in Practice: Build your own system, extend your existing systems through ML capabilities.
- Frameworks & Libraries: Tensorflow, Torch, SparkML, scikit-learn, Deeplearning4J, etc.
- Cognitive Services: Amazon Machine Learning, Microsoft Azure Machine Learning, IBM Watson, Google Prediction API, Mathematica, Splunk,
- Data Storage & Co: Hadoop world, Spark ecosystem, etc.
ML Conference Keynotes so far
When Microsoft released its AI chatbot Tay on Twitter in March 2016, Tay was supposed to learn to chat as ‘an average American teenage girl’. However, she quickly became sexist, racist, and anti-Semitic. Microsoft turned out to be overly naïve about the intentions of users who had to ‘train’ Tay.
In designing and developing technology, there are always risks involved. Next to calculating a design’s hard impacts, in terms of safety and health, also ‘soft’ impacts, such as undesirable consequences, deserve our attention. Today, logging off has become an illusion in our always-on world. Enormous data sets are generated every day. Algorithms not only have an important share in how we see the world, they also predict our future behavior and even influence our thoughts. Yet, neither algorithms nor data sets are ever neutral; on the contrary, users’ and developers’ biases slip into them. And still we rely on them on a daily basis. How can we anticipate and reduce undesirable consequences and pitfalls?
Understanding AI from the user and business perspective.
Machine learning, smart algorithms and autonomous products start to become realities of our daily life. But how do we need to design the artificial intelligence systems so they will be accepted, used and socially integrated in our societies and future businesses? Getting an idea why it is not about data but the situative relevance in data to become successful in data driven business and how to architecture the smart ecosystems so they will be beneficial for us as human beings will be an essential part of this presentation. Getting insights of how to design user centric AI systems from the user’s point of view will make you understand why it ́s not about technology but all about user centricity.