DeepLearning For Finance
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Introduction to Deep Learning
Introduction to Deep Learning
From Traditional Models to Deep Learning
The Multi-Layer Perceptron (MLP)
Automatic Differentiation: The Engine of Deep Learning
Computation Backends & Keras 3
GPUs and Deep Learning: When Hardware Matters
Keras Fundamentals: Models & Layers
Keras Matrix Operations: The Building Blocks
Activation Functions: Adding Non-linearity
Model Training Fundamentals
Travaux Pratiques
TP1: Building Neural Networks - From Simple to Custom Implementations
Recurrent Neural Networks
Recurrent Neural Networks
Sequential Data Processing: From MLPs to RNNs
Long Short-Term Memory Networks (LSTM)
Modern RNN Architectures
RNN Limitations: Computational Challenges
Travaux Pratiques
TP: Recurrent Neural Networks for Time Series Prediction
Training a Neural Network
Training a Neural Network
Understanding the Training Loop
Understanding Optimizers
Understanding Callbacks
Training Parameters and Practical Considerations
Travaux Pratiques
TP: Using Deep Learning Frameworks for General Optimization
TP: Impact of Callbacks on Training
Essential Building Blocks of Modern Neural Networks
Essential Building Blocks of Modern Neural Networks
Residual Connections and Gating Mechanisms
Convolutional Layers: From Images to Time Series
Neural Network Embeddings: Learning Meaningful Representations
Attention Mechanisms: Learning What to Focus On
Encoder-Decoder Architectures
Travaux Pratiques
Practical Assignment: Building a Transformer-Based Architecture for Time Series Forecasting
Code source
Training a Neural Network
Remi Genet
2025-02-18
Les cours de cette partie sont:
Training Parameters and Practical Considerations
Understanding key training parameters and practical considerations in deep learning.
Remi Genet
2025-02-18
Understanding Callbacks
Understanding callbacks in deep learning: how to monitor and control training processes.
Remi Genet
2025-02-18
Understanding Optimizers
Deep dive into optimization algorithms in deep learning, their mathematical foundations and practical applications.
Remi Genet
2025-02-18
Understanding the Training Loop
Deep dive into the fundamental training loop in deep learning, understanding how models learn step by step.
Remi Genet
2025-02-18
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Understanding the Training Loop