A Cabinet of Deep Learning Curiosities - Unconventional Techniques and Overlooked Methods
Explore unconventional deep learning techniques, from obscure hacks to overlooked best practices, that have proven surprisingly effective in real-world projects.
Artificial Intelligence: Miracle or Menace
Erörterung der Auswirkungen, Chancen und Risiken künstlicher Intelligenz auf unsere Zukunft aus der Perspektive eines Experten.
It's All About Machines and Creating Their Minds
Exploring user-centric AI design: How to create socially integrated, accepted, and beneficial machine learning systems for future businesses and daily life.
From Zero to Deep Learning Enhanced App
Practical insights on developing a Deep Learning Android app, from data collection to production deployment using TensorFlow, with tips on choosing the right approach and best practices.
Coding Deep Learning
Explore deep learning fundamentals, including matrix algebra and calculus, and get practical tips for using frameworks like Keras, PyTorch, and TensorFlow in this informative session.
Enterprise Tensorflow
Explore integrating TensorFlow models into Java enterprise environments, covering deployment, version control, and integration with popular server frameworks like Spring and Apache CXF.
Long Short-Term Memory - LSTM Models with TensorFlow
Dive into LSTM implementation using TensorFlow's Python API for natural language understanding. Learn the math and code behind this powerful RNN architecture in a hands-on session.
Natural Language Support with LUIS
Explore natural language understanding with LUIS for building conversational UIs and bots. Learn fundamental concepts, live coding demos, and practical applications in this comprehensive talk.
Algorithmic Architecture, Real-time AI and Alpha
Explore real-time AI trading systems, algorithmic architecture, and overcoming challenges in building scalable, robust AI for multi-instrument trading and cross-sector correlation analysis.
IoT and AI Software in Industry and Production
Explore the transformative potential of IoT data and AI in industry, focusing on Reinforcement Learning for industrial control tasks, from energy management to product quality optimization.
Commodity.AI
Explore the potential commoditization of AI, its challenges, and implications for businesses. Learn about cloud AI services and strategies for AI startups in a competitive landscape.
Machine Learning in the Browser
Explore the frontier of machine learning in web browsers, covering state-of-the-art libraries, implementation challenges, and performance optimization techniques for browser-based ML applications.
Too Many Ideas, Too Little Data
Explore strategies for building data pipelines from scratch, leveraging open data, web-sourced information, and collected data to create innovative data products that address customer needs in data-scarce environments.
How We Built a Job Recommender SaaS with Deep Learning to Disrupt the Job Market
Discover how deep learning and modern ML tools were used to create a multilingual job recommender system, revolutionizing job matching for a public employment service.
Machine Learning on Source Code
Explore Machine Learning on Source Code: trends, tools, and applications like deep code suggestions and structural embeddings. Learn how ML can improve developers' daily lives and gain insights from projects.
Kick-Start Your Understanding of Machine Learning with Python
Practical guide to building ML applications in Python, focusing on text classification using unsupervised and supervised learning techniques with visualization and deep learning examples.
Reinforcement Learning and Minecraft - ML Con Spring 2018
Explore reinforcement learning through Minecraft's AI platform, Project Malmo. Learn to solve problems using deep learning techniques in a unique experimental environment.
Gamified Control - China's Social Credit Systems
Explore China's Social Credit Systems: gamification, big data, and AI for behavior rating. Examine societal impacts and global implications of tech-driven social control.
Machine Learning Sucks
Explore common pitfalls in machine learning and strategies to overcome them, while acknowledging the field's challenges and potential for innovation in business and technology.
Quick Start with AI for Businesses
Strategies for businesses to quickly adopt AI, focusing on data collection, management involvement, and model capabilities. Proposes an embedded approach for efficient implementation and scaling.
Boost Your App with Machine Learning APIs
Discover how to enhance your app using pre-trained Machine Learning APIs for text, image, audio, and video analysis, with a live interactive demo showcasing practical applications.