Deep Learning World
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Topics & Overview 2020

Mastering the deep learning toolbox.

Deep Learning is no longer the cool new discipline. Instead it has become another tool in the toolbox of the data scientist – but a very important one! Without RNN, CNN etc. many applications that make our daily life better or help us to improve our business wouldn’t be possible. Take for example the German Federal State NRW: they are using neural networks to detect child pornography. Other organizations use it to detect cancer, translate text or inspect machines. It’s also important to understand how Deep Learning sits alongside traditional machine learning methods. As an expert you should know when and how to apply different methods for different applications. At the Deep Learning World conference, you will learn from other practitioners why they decided for a deep, transfer or reinforcement learning approach, what the analytical and technical but also organisational and economic challenges were and how they solved them. Take this opportunity and visit the two-day event to broaden your knowledge, deepen your understanding and discuss your questions with other Deep Learning experts.

 

  • 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)
    • … 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
    • Attention Mechanisms
    • … and further.
  • Tools & Frameworks
    • TensorFlow
    • Scikit-learn
    • Caffe
    • Torch / PyTorch
    • CNTK
    • Deeplearning4j
    • Keras
    • MXNet
    • ONNX
    • … and others.
  • Trending
    • AutoML
    • DataOps (Data Operations)
    • Data & AI Governance
    • Augmented Analytics & Intelligence
    • AGI vs. ANI (Strong vs. Weak AI)
    • … and more.

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