Bayesian Optimization
Bayesian Optimization: A Comprehensive Guide Introduction Bayesian Optimization (BO) is an efficient method for optimizing black-box functions that are expensive to evaluate. It is widely used in hyperparameter tuning for….
Tag: Hyperparameter Tuning
AutoML Tools
AutoML Tools: A Comprehensive Guide Introduction to AutoML Automated Machine Learning (AutoML) is an advanced approach that simplifies and automates the process of building, training, and deploying machine learning models…..
Image Classification with CNNs
Image Classification with Convolutional Neural Networks (CNNs) Introduction Image classification is a fundamental task in computer vision where an algorithm assigns a label to an image from a predefined set….
Topic Modeling (LDA)
Topic Modeling (LDA – Latent Dirichlet Allocation) Introduction Topic modeling is an unsupervised machine learning technique that identifies the underlying themes (topics) in a large collection of text documents. One….
Evaluating Time Series Models
Evaluating Time Series Models 1. Introduction to Time Series Model Evaluation Time series forecasting models predict future values based on historical data. However, before deploying a model, it is crucial….
Feature Engineering for Time Series
Feature Engineering for Time Series Data 1. Introduction to Feature Engineering in Time Series Feature engineering is a crucial step in time series forecasting and machine learning. It involves transforming….
LSTMs for Time Series
Long Short-Term Memory Networks (LSTMs) for Time Series Forecasting 1. Introduction to LSTMs for Time Series Forecasting Long Short-Term Memory (LSTM) networks are a type of Recurrent Neural Network (RNN)….
Working with Scikit-learn
Scikit-learn (often abbreviated as sklearn) is one of the most popular machine learning libraries in Python. It provides simple and efficient tools for data analysis and modeling, including classification, regression,….
Introduction to Neural Networks
Introduction to Neural Networks: Detailed Explanation A Neural Network (NN) is a computational model inspired by the way biological neural networks in the human brain process information. It is a….
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Gradient Boosting (XGBoost, LightGBM, CatBoost) in Machine Learning 1. Introduction to Gradient Boosting Gradient Boosting is a powerful ensemble learning technique used in machine learning for classification and regression tasks…..