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Michael Brenndoerfer

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Mostly thoughts on data, AI, software engineering—and where they intersect with finance, business, and entrepreneurship.

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Language AI Handbook

CRF Training: Forward-Backward Algorithm, Gradients & L-BFGS Optimization

Master Conditional Random Field training with the forward-backward algorithm, gradient computation, and L-BFGS optimization for sequence labeling tasks.

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CRF Training: Forward-Backward Algorithm, Gradients & L-BFGS Optimization

Stochastic Gradient Descent: From Batch to Minibatch Optimization

Multilayer Perceptrons: Architecture, Forward Pass & Implementation

Linear Classifiers: The Foundation of Neural Networks

Dropout: Neural Network Regularization Through Random Neuron Masking

Viterbi Algorithm: Dynamic Programming for Optimal Sequence Decoding

Weight Initialization: Xavier, He & Variance Preservation for Deep Networks

Adam Optimizer: Adaptive Learning Rates for Neural Network Training

Momentum in Neural Network Optimization: Accelerating Gradient Descent

Gradient Clipping: Preventing Exploding Gradients in Deep Learning

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Latest

CRF Training: Forward-Backward Algorithm, Gradients & L-BFGS Optimization

Stochastic Gradient Descent: From Batch to Minibatch Optimization

Multilayer Perceptrons: Architecture, Forward Pass & Implementation

Linear Classifiers: The Foundation of Neural Networks

Dropout: Neural Network Regularization Through Random Neuron Masking

Viterbi Algorithm: Dynamic Programming for Optimal Sequence Decoding

Weight Initialization: Xavier, He & Variance Preservation for Deep Networks

Adam Optimizer: Adaptive Learning Rates for Neural Network Training

Momentum in Neural Network Optimization: Accelerating Gradient Descent

Gradient Clipping: Preventing Exploding Gradients in Deep Learning

Explore by Topic

Stay updated