Odsc Europe 2018 (open Data Science Conference) (part Two)

Category: Tutorial

Posted on 2019-07-10, by everest555.


ODSC Europe 2018 (Open Data Science Conference) (Part Two)
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 20 Hours | 21.2 GB
Genre: eLearning | Language: English


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 – 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


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