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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

Reinforcement Learning in Robotics

Last Updated: 27 June 2025

Reinforcement Learning (RL) has become a transformative approach in robotics, enabling robots to learn complex behaviors through trial and error interactions with their en...read more

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Artificial Intelligence

mlr3 Package in R

Last Updated: 27 June 2025

The mlr3 package is a modern machine learning framework for R that simplifies building, evaluating and tuning machine learning models. It provides a unified interface for ...read more

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R Machine-Learning

R Machine Learning

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

spaCy for Natural Language Processing

Last Updated: 30 June 2025

spaCy is an open-source library for advanced Natural Language Processing (NLP) in Python. Developed by Matthew Honnibal and Ines Montani, spaCy is designed to be fast, eff...read more

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Natural-language-processing

Generalized Method of Moments (GMM) in StatsModels

Last Updated: 30 June 2025

Generalized Method of Moments (GMM) is a flexible estimation technique that uses moment conditions relationships expected to hold in the data to estimate model parameters....read more

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Panel Data Analysis in StatsModels

Last Updated: 30 June 2025

Panel data (also known as longitudinal or cross-sectional time-series data) consists of observations on multiple entities (such as individuals, firms, or states) tracked o...read more

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Last Updated: 01 July 2025

SymPy (short for Symbolic Python) is a core Python library for symbolic mathematics. It enables exact computation with algebraic expressions, calculus, matrices and equati...read more

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Python SymPy-Stats

CatBoost with Sparse Data

Last Updated: 30 June 2025

CatBoost is a gradient boosting library that naturally handles sparse data as it has many zero or missing values without extra preprocessing. It supports sparse matrix for...read more

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Nesterov Adaptive Moment Estimation (Nadam)

Last Updated: 30 June 2025

Nadam (Nesterov accelerated Adaptive Moment Estimation) combines the strengths of Adam which uses adaptive learning rates and momentum with Nesterov momentum which looks a...read more

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Building a Custom Training Loop with Autograd

Last Updated: 01 July 2025

Autograd is PyTorch’s automatic differentiation engine. It allows you to compute gradients automatically by tracking operations on tensors. Training machine learning model...read more

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Pooled OLS Regression

Last Updated: 01 July 2025

Pooled OLS treats panel data as if it were one large cross sectional dataset, ignoring any time or entity specific effects. In this method all observations are pooled toge...read more

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Introduction to Pyro

Last Updated: 01 July 2025

Pyro is an open source probabilistic programming library built on PyTorch. Pyro lets you define complex probabilistic models using Python code, combine them with deep lear...read more

Data Science Library

AI-ML-DS With Python

Feature Engineering for XGBoost Models

Last Updated: 01 July 2025

Feature engineering is the process of transforming raw data into meaningful features that better represent the underlying problem to predictive models, resulting in improv...read more

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Machine Learning

AI-ML-DS With Python

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