Check out these 7 Matplotlib tricks to help better visualize your machine learning models.
Making Sense of Text with Decision Trees
Learn how to build decision trees for text data and apply them to spam email detection, incorporating the use of text representation techniques like TF-IDF and embeddings.
How to Interpret Your XGBoost Model: A Practical Guide to Feature Importance
This article provides a practical exploration of XGBoost model interpretability by providing a deeper understanding of feature importance.
Grok’s Share and Claude’s Leak: 5 Things We Can Learn From System Prompts
This article introduces how system prompts, through specific examples from the above-mentioned prompts, can reveal 5 specific lessons.
7 Pandas Tricks for Time-Series Feature Engineering
This article will explore 7 practical Pandas tricks that can help transform your time-series data, which can help lead to enhanced models and more powerful prediction.
Time-Series Transformation Toolkit: Feature Engineering for Predictive Analytics
This article shows a moderately advanced approach to constructing meaningful temporal features and applying various transformations for predictive analytics purposes, using feature engineering.
A Gentle Introduction to Q-Learning
Get a gentle introduction to one of the most widely used reinforcement learning algorithms to learn optimal courses of action through trial and error.
Building a Decoder-Only Transformer Model Like Llama-2 and Llama-3
The large language models today are a simplified form of the transformer model. They are called decoder-only models because their role is similar to the decoder part of the transformer, which generates an output sequence given a partial sequence as input. Architecturally, they are closer to the encoder part of the transformer model. In this […]
Building a Transformer Model for Language Translation
The Transformer architecture, introduced in 2017, revolutionized sequence-to-sequence tasks like language translation by eliminating the need for recurrent neural networks. Instead, it relies on self-attention mechanisms to process input sequences. In this post, you’ll learn how to build a Transformer model from scratch. In particular, you will understand: How self-attention processes input sequences How transformer […]
How to Diagnose Why Your Regression Model Fails
This article explores identifying and understanding common reasons why regression models in machine learning may fail to perform well, from data quality issues to poorly defined model configurations.