Remaining Challenges in Deep Learning Based NLP
Explores remaining challenges in Deep Learning-based NLP, including data limitations, performance metrics, robustness issues, representation problems, and lack of interpretability, despite recent advancements and media hype.
Bridging the Gap Between AI and UI
Explore methods for understanding AI model predictions and their input features, with a focus on RNN in NLP. Learn novel ideas for incorporating visualizations to enhance user experience and retention.
AI and Advanced Analytics Applied at Raffeisen Bank International AG
Explore AI and advanced analytics applications in banking, focusing on Raffeisen Bank International's innovative approaches to data-driven decision-making and customer service enhancement.
Data Science for Business - Repeatable and Objective Data Science Process
Explore the Team Data Science Process (TDSP) for efficient predictive analytics and AI integration in business processes, focusing on agile methodology and practical implementation strategies.
I Need Data - For Research
Explore the challenges of obtaining quality data for AI applications in security and other fields, focusing on data acquisition methods and assessing data quality for effective research and development.
When Humans Teach Machines
Explore an interactive DIY tool for non-data scientists to train and deploy classifiers, simplifying topic identification in large document sets with minimal data collection and quick model training and tuning.
Building a Large Music Recommender Leveraging AI, Deep Learning and Human Expertise
Explore Pandora's sophisticated music recommendation system, combining AI, deep learning, and human expertise to deliver personalized listening experiences based on vast user data and musicological insights.
Practicing Data Science in the Cloud
Explore end-to-end Machine Learning pipelines in the cloud, from data processing to model deployment, with practical insights on choosing environments and optimizing workflows.
Snap ML - A Highly-Accelerated, Scalable Software Library for Machine Learning
Discover Snap ML, a high-performance framework for training generalized linear models. Learn about its GPU acceleration, pipelining, and distributed computing capabilities for faster machine learning on large-scale datasets.
Building a Data-Oriented Future
Explore data-oriented engineering's impact on software development and its potential to enhance user value from computers, with insights on Unity's approach and future-proofing strategies.
Data, Design, Code
Explore the process of creating web-based data visualizations, from topic selection and data preparation to designing visual encodings, with insights on using D3.js for custom, impactful visualizations.
End-to-End Deep Learning Pipeline for Self-Driving Cars
Explore the end-to-end deep learning pipeline for self-driving cars, covering data collection, processing, model training, evaluation, and deployment, with insights on common mistakes and future developments.
Data-Driven Process Optimisation at Mondi
Explore data-driven process optimization techniques, from data collection to model deployment and management, using real-world examples from Mondi's manufacturing operations.
Building a Data Platform with Apache Spark on Kubernetes
Explore building a data platform using Apache Spark on Kubernetes, focusing on challenges and solutions for managing on-demand Spark clusters and Jupyter Notebooks in containerized environments.
Are You on the Edge or Still in the Cloud
Explore edge computing vs. cloud processing, understanding key concepts, benefits, and considerations for optimal data processing in modern applications.
Data Science in Action
Explore real-world applications of data science, from label data to unsupervised machine learning, with practical examples in wind energy, object detection, and automotive industries.
Kandinsky Patterns for Visual Concept Learning
Explore visual concept learning through Kandinsky patterns, focusing on medical image interpretation, symmetry, heatmaps, and decision trees for enhanced pattern recognition and analysis.
Real Data vs. Anonymization
Explore data anonymization techniques and their impact on data quality, privacy, and utility in real-world applications. Learn to balance data protection with analytical value.
Program Synthesis
Explore program synthesis techniques including data wrangling, enumerative search, and superoptimization. Learn about tools like FlashFill and PROSE for automated code generation and optimization.
How to Make Money with Data Analytics in Industrial Use Cases
Explore industrial data analytics monetization strategies, from algorithm development to model lifecycle management, with insights on bridging data science and engineering gaps.
Edge Computing Done by Your Network
Explore edge computing in network components, real-life use cases across industries, and containerized application management. Includes a live demo showcasing practical implementations and possibilities.