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AI-ML-DS With Python

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Reinforcement Learning with Intrinsic Motivation

Last Updated: 24 June 2025

In traditional reinforcement learning, an agent learns by receivingrewards from the environment for example, a robot gets a point for reaching a goal, or a game-playing AI...read more

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AI-ML-DS With Python

Last Updated: 25 June 2025

XGBClassifier is an efficient machine learning algorithm provided by the XGBoost library which stands for Extreme Gradient Boosting. It is widely used for solving classifi...read more

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Machine Learning

Machine Learning

AI-ML-DS With Python

Curiosity-Driven Exploration in Reinforcement Learning

Last Updated: 25 June 2025

Curiosity-driven exploration is approach in reinforcement learning (RL) that addresses the challenge of sparse or delayed rewards by introducing internal, self-generated i...read more

AI-ML-DS With Python

XGBoost multiclass classification

Last Updated: 28 June 2025

XGBoost(Extreme Gradient Boosting) is a scalable and flexible gradient boosting framework that has consistently delivered top performance in both academic research and dat...read more

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Machine Learning

AI-ML-DS With Python

Scikit Learn Tutorial

Last Updated: 27 June 2025

Scikit-learn (also known as sklearn) is a widely-used open-source Python library for machine learning. It builds on other scientific libraries like NumPy, SciPy and Matplo...read more

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Machine Learning

Data Science Library

AI-ML-DS With Python

Language models are few-shot learners

Last Updated: 25 June 2025

Few-shot learning is a machine learning approach where a model learns to perform new tasks or recognize new categories using only a small number of labeled examples, rathe...read more

Machine Learning

Machine Learning

AI-ML-DS With Python

Flexible Clustering

Last Updated: 25 June 2025

Clustering is a fundamental task in unsupervised machine learning that involves grouping similar data points into clusters. Flexible Clustering refers to a set of modern t...read more

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Machine Learning

Machine Learning

AI-ML-DS With Python

Online and Offline Reinforcement Learning

Last Updated: 27 June 2025

Reinforcement Learning (RL) agents learn optimal behaviors by maximizing cumulative rewards through experience. The way agents acquire and use data divides RL into two maj...read more

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AI-ML-DS With Python

Page-Hinkley Method

Last Updated: 28 June 2025

The Page-Hinkley (PH) method is a statistical change detection algorithm used to detect sudden changes in the average mean of a time series or data stream. It is widely us...read more

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AI-ML-DS With Python

Attention and Memory in Deep Learning

Last Updated: 28 June 2025

In deep learning attention and memory are two important ideas that help machines understand and work with information more effectively. These ideas are inspired by how the...read more

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AI-ML-DS With Python

Text Classification Using NLTK

Last Updated: 28 June 2025

Text classification is a fundamental task in Natural Language Processing (NLP) that involves assigning categories or labels to text based on its content. One of the most a...read more

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Natural-language-processing

AI-ML-DS With Python

Grouped Query Attention (GQA)

Last Updated: 26 June 2025

Grouped Query Attention (GQA) is an optimization technique for transformer models that balances computational efficiency and model performance. Inspired by the multi-head ...read more

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AI-ML-DS With Python

Sequential vs Functional API in Keras

Last Updated: 26 June 2025

Keras provides two main ways to build deep learning models: the Sequential API and the Functional API. Both are part of the Keras high-level API, but they differ in terms ...read more

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AI-ML-DS With Python

Adaptive Optimization in ML

Last Updated: 28 June 2025

Adaptive Optimization in Machine Learning is a set of techniques that automatically adjust the learning rate during training. Unlike traditional methods like basic SGD tha...read more

Machine Learning

AI-ML-DS With Python

Variational Inference in Bayesian Neural Networks

Last Updated: 30 June 2025

Bayesian Neural Networks (BNNs) extend traditional neural networks by treating weights asprobability distributionsrather than fixed values. This approach quantifies uncert...read more

AI-ML-DS With Python

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