ODSC Europe 2018 (Open Data Science Conference)

ODSC Europe 2018

Royalties for this video set help fund the ODSC Grant Award for open source data science projects.

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 science 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:

• Machine Learning in R Part I--Jared Lander
• Machine Learning in R Part II--Jared Lander
• Machine learning and statistics: Don't mind the gap--Thomas Wiecki, PhD
• Deep Learning for Developers--Julien Simon
• Target Leakage in Machine Learning--Yuriy Guts
• Ensemble Models Demystified--Kevin Lemagnen
• Towards Interpretable Deep Learning--Dr. Wojciech Samek
• Delivering Machine Learning at Scale ‚Äì An agile approach to Model Governance--Thomas Cronin
• An Introduction to Active Learning--Jennifer Prendki, PhD
• Introduction to Machine Learning--Andreas Mueller, PhD
• Linguistics in NLP: why so complex?--Mariana Romanyshyn
• Deep Learning for Mail Processing--Alexandre Hubert
• Introduction to Automatic and Interpretable Machine Learning with H2O and LIME--Jo-fai Chow, PhD
• Elegant Machine Learning workshop with Julia and Flux--Avik Sengupta
• Deep Learning for Recommender Systems--Oliver Gindele, PhD
• Intermediate Machine Learning with scikit-learn--Andreas Mueller, PhD
• Multivariate Time Series Forecasting Using Statistical and ML Models--Jeffrey Yau
• Democratize Conversational AI--Scaling Academic Research to Industrial Applications--Pei-Hao, PhD
• Racing an Autonomous Toy Car from Scratch--Constant Bridon
• How to Learn Many, Many Labels with ML--Dr. Michael Swarbrick Jones
• Deploying Large Spark Models and scoring in Real time at Scale--Subhojit Banerjee
• Resolving Corporate Entities in the International Supply Chain Graph--Timothy Garnett
• GPUs Transforming Open Source Integration in Intelligent IoT Networks--Dr. Mo Haghighi
• Automated ML: Drink your Coffee and Let the Machine Work for You--Marius Lindauer, PhD
• Learning a Universal Latent Space for Accelerated Drug Discovery--Mason Victors
• Making Sense of Twitter @Bloomberg For Finance--Edgar Meij

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:

• Introduction to Data Science--A Practical Viewpoint--Jesus Rogel-Salazar
• Accelerate AI | Fuelling the AI Revolution with Gaming--Alison Lownde
• How to Play Fantasy Sports Strategically (and Win)--Dr. Martin Haugh
• Understanding Unstructured Data with Language Models--Alex Peattie
• Handling Missing Data in Python/Pandas and R--Alexandru Agachi
• Competitive Model Stacking: An Introduction to Stacknet Meta Modelling Framework--Marios Michailidis, PhD
• Inside the Black Box: How Does a Neural Network Understand Names?--Kfir Bar, PhD
• AI Nudging: Data, Privacy, and Manipulation--Karina Vold, PhD
• Zen and the Art of Model Maintenance--Joseph Blue
• Building Interactive Dashboards in Python: A Hands-on Introduction for Data Scientists--Dr. Pascal Bugnion
• Multi-task Learning--Shioulin Sam, PhD
• A Gentle Introduction to Survival Models with Applications in Python and R--Violeta Misheva, PhD
• Learning Functions: Understanding Gradient Descent, Backpropagation, and Vanishing Gradients--Dr. John D. Kelleher
• Big Data Trade FX & Python in Finacial Markets--Saeed Amen
• Telling Human stories with Data--Alan Rutter
• From Numbers to Narrative: Data Storytelling--Isaac Reyes

Data Science, Management, And Business

Data science is permeating every industry as adoption gathers pace. The management and practice of data science will become increasingly strategically important to all industries including finance and healthcare. Hear from leading experts on important topics including:

• Accelerate AI | The people problem of Artificial intelligence--Hugo Pinto
• Accelerate AI | Your brain is too small to manage your business--Christopher Bishop
• AI Challenges and Opportunities--Luciano Floridi
• Accelerate AI | AI For Good--Fact Or Fiction?--Dr Sybil Wong
• Accelerate AI | Personalising finance--Igor Volzhanin
• Accelerate AI | AI in Business Forecasting: Lessons from Building an Intelligent Cashflow Engine--Johnnie Ball
• Peer detection with Massive Payment Transaction Network--Zhe Sun
• Data Science Driven Digital Transformation--Kanishka Bhattacharya, PhD
• Accelerating AI Innovation in Banking at Scale--Jesper Nordstr√∂m
• Accelerate AI | AI in Banking : Challenges, Opportunities and Future--Arif Khan
• Accelerate AI | Data Science for Vaccines Research and Development--Dr Duccio Medini

Please see our table of contents for a full list of videos