Deep Learning World
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Topics & Overview 2022

Mastering the deep learning toolbox.

Deep Learning World is back on stage! After two years of virtual conferences the European AI community meets again in Berlin to present the successes of applied deep learning and the challenges with deep learning methods. Especially during the Corona crisis neural networks proved to be a valuable tool: to detect COVID-19 on CT images or even in voice recordings; to predict the spread of the virus; to identify people not wearing masks in the crowd; or even to model the structure of proteins and thus accelerating the development of new drugs. Deep learning nowadays is everywhere: it synthesizes media for the entertainment industry; drones use it to detect anomalies e.g. on wind turbines and; logistics apply it to predict demand and supply. At Deep Learning World Europe 2022 experts from leading-edge companies will demonstrate the power of deep learning with real-world business case studies, explain promising new methods and tools in deep dive sessions and provide an outlook on the even more exciting future of deep learning.

  • Methods
    • Long Short-Term Memory (LSTM) Neural Networks
    • Recurrent Neural Networks (RNN)
    • Convolutional Neural Networks (CNN)
    • Generative Adversarial Networks (GAN)
    • Deep Reinforcement Learning (DRL)
    • Capsule Networks (CapsNet)
    • Graph Neural Networks (GNN)
    • … and more
  • Applications
    • Image & Object Recognition
    • Speech, Gesture & Character Recognition
    • Natural Language Processing & Generation
    • Entity Recognition & Text Extraction
    • Automatic Translation & Caption Generation
    • Forecasting & Event Detection
    • Visual Inspection & Action Recognition
    • Autonomous Driving & Flying
    • Recommender Systems
    • Chat Bots & Virtual Agents
    • … and more.
  • Industries
    • Healthcare & Pharmacy
    • Finance & Insurance
    • Marketing & Sales
    • Manufacturing & Logistics (Industry 4.0)
    • Travel & Mobility
    • Media & Entertainment
    • … and others.
  • Challenges
    • Word & Graph Embeddings
    • Model Interpretability & Visualization
    • Transfer & One-Shot-Learning
    • Model Factories & Management
    • Model Bias & Overfitting
    • Distributed & Federated Learning
    • Transformers & Attention Mechanisms
    • Explainable, Responsible & Sustainable AI (xAI, rAI, sAI)
    • Self-Supervised Learning
    • … and further.
  • Tools & Frameworks
    • TensorFlow
    • Scikit-learn
    • Caffe
    • Torch / PyTorch
    • CNTK
    • Deeplearning4j
    • Keras
    • MXNet
    • ONNX
    • BERT
    • GPT-3
    • … and others.
  • Trending
    • AutoML
    • DataOps, MLOps & ModelOps
    • Data & AI Governance
    • Augmented Analytics & Intelligence
    • AGI vs. ANI (Strong vs. Weak AI)
    • Foundation Models
    • … and more.

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