Learn about fine-tuning neural networks.
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Baeldung Author
Saulo Barreto
Currently, I'm a PhD student at the Université de Lorraine, France, in which I'm working on tensor-based approaches for polarization. However, I'm also keen on delving into various subjects within the realm of AI, spanning from Generalization Theory to practical applications in Computer Vision, as well as any real advancements that contribute to the progression of the field.
Here's what I've written (so far):
Baeldung on Computer Science
- All
- Machine Learning (15)
- Math and Logic (6)
- Deep Learning (5)
- Programming (4)
- Computer Vision (3)
- Methodology (1)
- Data Science (1)
Differences Between Backpropagation and Feedforward Networks
Filed under Deep Learning, Machine Learning
Learn the differences between backpropagation and feedforward neural networks.
Real-Life Examples of Supervised Learning and Unsupervised Learning
Filed under Deep Learning, Machine Learning
Explore some real-life examples of supervised and unsupervised learning.
Markov Decision Process: How Does Value Iteration Work?
Filed under Machine Learning
Learn how to implement a dynamic programming algorithm to find the optimal policy of an RL problem, namely the value iteration strategy.
Choosing a Learning Rate
Filed under Machine Learning
Explore different strategies to update the weights during the training phase of any machine learning model.
How Do “20 Questions” AI Algorithms Work?
Filed under Machine Learning
Learn how we can implement the 20 Questions Game using a nonparametric model called a decision tree.
High-Level Languages vs. Low-Level Languages
Filed under Programming
Explore the differences between high-level and low-level languages.
Why Mini-Batch Size Is Better Than One Single “Batch” With All Training Data
Filed under Deep Learning, Machine Learning
Learn the main differences between using the whole dataset as a batch to update the model and using a mini-batch
Clean Code – Formatting
Filed under Programming
Learn about good practice for code formatting.