| Sumario: | ODSC The Open Data Science Conference has established itself as the leading conference in the field of applied data science. Each ODSC event offers a unique opportunity to learn directly from the core contributors, experts, academics and renowned instructors helping shape the field of data science and artificial intelligence Presentations cover not only data science modeling but also the languages and tools needed to deploy these models in the real world such as TensorFlow, MXNet, scikit-learn, Kubernetes, and many more. Our conferences are organized around focus areas to ensure our attendees are at the forefront of this fast emerging field and current with the latest data science languages, tools, and models. You’ll find in our East 2018 video catalog some of our most popular focus areas including: Deep Learning and Machine Learning Over the last 5 years, we have seen incredible advances in the field of data scientist thanks to breakthroughs in neural networks, transfer learning, reinforcement learning, and generative adversarial networks (GANs) to name a few. With the advent of Google Voice, Alexa, and other voice assistants, presentations on enabling technologies like NLP, RNNs, and LSTM are popular. Some session to note: Distributed TensorFlow using Kubernetes Deep Learning Pipelines for Big Images Machine Learning and Natural Language Processing for Detecting Fake News Long-Term Time Series Forecasting with Recurrent Neural Networks A Breakthrough for Natural Language Transfer Learning: Applications for natural language understanding Challenges and Opportunities in Applying Machine Learning Effective Transfer Learning for NLP Developing Machine Learning Solutions with Plugin Machine Intelligence for PDI Distributed Tensorflow: Scaling Your Model Training Core Data Science and Data Visualization As data science advances at a rapid pace, core skills are more important than ever. Our sessions range from beginner to advanced level for core topics. Additionally, data and models need to be actionable and data visualization remains a key skill in any data scientist's toolkit. Some session of note include: Bayesian Statistics Made Simple Gradient Descent, Demystified Comparing Models Using Resampling and Bayesian Methods Next Generation Indexes For Big Data Engineering Probabilistic Programming with PyMC3 Racial Bias in Facial Recognition Software Visualization throughout the Data Science Workflow: Datafy All The Things Data Science, Management...
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