Curriculum Learning - Learn Data Science with Travis

Curriculum-Learning

Curriculum Learning is an educational strategy inspired by human learning processes, where models are trained on tasks in a structured order based on difficulty. Instead of exposing a model to a complete dataset with varying complexities from the start, Curriculum Learning begins with simpler examples and gradually introduces more challenging ones. This approach allows models to build foundational knowledge before tackling complex tasks, leading to improved performance and efficiency. It has been successfully applied in various fields, including image classification, reinforcement learning, and medical image analysis, demonstrating its effectiveness in enhancing learning outcomes for artificial intelligence systems.

How to Improve Your Network Performance by Using Curriculum Learning

Towards Data Science

Curriculum learning describes a type of learning in which you first start out with only easy examples of a task and then gradually increase the task difficulty. We humans have been learning according…...

Applying Curriculum Learning to Medical Images

Towards Data Science

General Overview. In this study, I worked with a team of researchers to apply curriculum learning to improve the accuracy of a deep learning model for classifying colorectal cancer images. The full…

Curriculum Learning With Unity ML-Agents

Towards Data Science

Curriculum Learning With Unity ML-Agents.

Learning Engineering: Merging Science and Data to Design Powerful Learning Experiences

Towards Data Science

Learning is an organic process where the seeds of knowledge are slowly and steadily been planted and engraved into the minds. This seeds of knowledge eventually bear fruit when it is put into action…

Plotting Learning Curves

Scikit-learn Examples

Plotting Learning Curves In the first column, first row the learning curve of a naive Bayes classifier is shown for the digits dataset. Note that the training score and the cross-validation score are ...

Systematic Learning Matters

Towards Data Science

During the first 20 years of my life, I was a passive learner. Schools and college had been my major knowledge source: Every semester, faculty members provided a syllabus with studying plans for each…...

Transfer Learning

Analytics Vidhya

As humans growing and learning in day-to-day activities right from childhood. As humans acquire knowledge by learning one task. By using the same knowledge we tend to solve the related task. Say in…

Gentle Introduction to Knowledge Representation Learning

Towards Data Science

Knowledge representation learning (KRL) mainly focus on the process of learning knowledge graph embeddings, while keeping the semantic similarities. This has proven extremely useful, as feature…

Q-Learning

Towards Data Science

Welcome to my column on reinforcement learning, where I spend some time going over some very interesting concepts revolving around the nature of learning with a computational approach. As with most…

Continual Learning: A Primer

Towards Data Science

Plus paper recommendations Continue reading on Towards Data Science

Real Life Meta-Learning: Teaching and Learning to Learn

Towards Data Science

Teaching and learning are two incredibly crucial skills we use throughout our lives. Let’s learn how to optimize these skills with reinforcement learning and meta-learning!

Q-Learning

Dive intro Deep Learning Book

In the previous section, we discussed the Value Iteration algorithm which requires accessing the complete Markov decision process (MDP), e.g., the transition and reward functions. In this section, we ...