Reinforcement Learning Algorithms - Value-based methods - [Part 5] Tabular Learning and the Bellman Equation Value, state, and optimality We defined this value as an expected total reward (option...

Reinforcement Learning Algorithms - [Part 4] The taxonomy of RL methods All the methods in RL can be classified into various groups: Model-free or model-based Value-based or po...

Reinforcement Learning Algorithms - [Part 3] The OpenAI Gym API and Gymnasium Install requierment gymnasium[atari]==0.29.1 gymnasium[classic-control]==0.29.1 gymnasium[accept-rom-license]==0.2...

Reinforcement Learning Algorithms - [Part 2] RL formalisms The following diagram shows two major RL entities — agent and environment — and their communication channels — actions , ...

Reinforcement Learning Algorithms - [Part 1] An introduction to RL RL is an area of machine learning that deals with sequential decision-making, aimed at reaching a desired goal. An RL problem is...

NLP - Getting started [Part 6] Information extraction Information extraction in natural language processing (NLP) is the process of automatically extracting structured information from unstructur...

NLP - Getting started [Part 5] Neural Networks Neural Networks (NNs) are a foundational concept in machine learning, inspired by the structure and function of the human brain. At their core, NNs...

NLP - Getting started [Part 4] Vector Space Model The Search Task Given a query and a corpus , find relevant items query: a textual description of the user’s information need corpus: ...

NLP - Getting started [Part 3] Word Sense Disambiguation Word sense disambiguation (WSD) is the task of determining the correct meaning of a word in a given context. It is a common problem in nat...

NLP - Getting started [Part 2] Bag of Words Model Bag of Words (BoW) is a Natural Language Processing strategy for converting a text document into numbers that can be used by a computer program. ...