Stock Market Prediction
Stock Market Prediction: A Comprehensive Guide Introduction Stock market prediction is the process of using historical stock data, financial indicators, machine learning (ML), and deep learning techniques to forecast the….
Tag: Stock Market Prediction
Sentiment Analysis
Sentiment Analysis – A Comprehensive Guide 1. Introduction to Sentiment Analysis Sentiment Analysis, also known as opinion mining, is a Natural Language Processing (NLP) technique that determines the emotional tone….
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)….
Autoregressive Models
Autoregressive (AR) Models: A Comprehensive Guide 1. Introduction to Autoregressive (AR) Models Autoregressive (AR) models are one of the fundamental models used in time series forecasting. The AR model predicts….
Prophet for Time Series Forecasting
Prophet for Time Series Forecasting: A Detailed Guide 1. Introduction to Prophet Prophet is an open-source forecasting tool developed by Facebook (Meta). It is designed to handle time series forecasting….
Exponential Smoothing Methods
Exponential Smoothing Methods for Time Series Forecasting 1. Introduction to Exponential Smoothing Exponential Smoothing is a time series forecasting technique that applies exponentially decreasing weights to past observations. It is….
k-Nearest Neighbors (k-NN)
k-Nearest Neighbors (k-NN) Algorithm in Machine Learning 1. Introduction to k-Nearest Neighbors (k-NN) k-Nearest Neighbors (k-NN) is a supervised learning algorithm used for classification and regression tasks. It is a….
Support Vector Machines (SVM)
Support Vector Machines (SVM) in Machine Learning 1. Introduction to Support Vector Machines (SVM) Support Vector Machine (SVM) is a supervised learning algorithm used for classification and regression problems. SVM….