Machine Learning Expedition

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Machine Learning Expedition

An Introduction to Proximal Policy Optimization (PPO) in Reinforcement Learning

Proximal Policy Optimization (PPO) is an advanced reinforcement learning algorithm that has become very popular in recent years. In this comprehensive guide, we will cover: * What is PPO and how it relate to reinforcement learning * The key components and techniques used in PPO * Actor-critic method * Clipping the objective function * Adaptive

Top Machine Learning Algorithms for Real-World Machine Learning

Top Machine Learning Algorithms for Real-World Machine Learning

Linear Regression Linear regression is one of the most fundamental and commonly used statistical and machine-learning techniques. At its core, linear regression involves fitting a straight line through a set of data points to be able to make predictions about future data points. The basic idea behind linear regression is

Introduction to Word2Vec

Word2vec is a popular group of related models used to produce word embeddings. Word embeddings are vector representations of words that capture semantic meaning allowing words with similar meanings to have similar representations. Word2vec models are shallow, two-layer neural networks trained on large amounts of text data to reconstruct linguistic

Finding the Needles in the Haystack: A New Approach to Anomaly Detection in Tabular Data

Anomaly detection is like searching for a needle in a haystack. It's about identifying unusual data points that stand out from the crowd, often indicating errors, fraud, or unexpected events. But what if you have limited data, or need to understand why something is anomalous? That's

Understanding RuleFit: The Algorithm That Combines Decision Trees and Linear Models

The RuleFit algorithm stands out as a unique approach in the realm of machine learning. It ingeniously combines the interpretability of decision trees with the simplicity and effectiveness of linear models. In this blog, we'll dive deep into what RuleFit is, how it works, and its practical applications.

Parallelizing Python Code

Python has become the go-to language for a vast array of tasks, from machine learning to data analysis and scientific computing. But when it comes to time-intensive tasks like model training or large-scale simulations, even the most powerful hardware can feel sluggish. This is where parallel processing comes in, offering

Conformal Prediction: A light introduction

In the ever-evolving world of machine learning, where algorithms are tasked with making predictions about complex systems, the ability to accurately quantify uncertainty is paramount. This is where conformal prediction (CP) steps in, offering a powerful framework for building trust and reliability in our models. What is Conformal Prediction? Conformal