Forecast Crypto Market with Time Series & Machine Learning
Learn how to forecast cryptocurrency market with Prophet model, time series decomposition, Random Forest, and XGBoost
3.78 (9 reviews)
4,042
students
3.5 hours
content
Feb 2025
last update
$19.99
regular price
What you will learn
Learn basic fundamentals of cryptocurrency market forecasting, such as getting to know crypto market characteristics and forecasting models that will be used
Learn how to build forecasting model using Prophet
Learn how to build forecasting model using time series decomposition
Learn how to build forecasting model using machine learning, specifically Random Forest and XGBoost algorithm
Learn how to evaluate the accuracy and quality of the forecasting models using prediction interval coverage, component analysis, and feature importance analysis
Learn math and logics behind prophet forecasting model, such as getting to know trend factor, seasonality component, and holiday component
Learn math and logics behind time series decomposition model, such as getting to know trend component, seasonal component, and residual component
Learn how to split dataset using Random Forest algorithm and learn how to calculate Gini Impurity
Learn several factors that can potentially impact cryptocurrency market, such as circulating supply, transaction volume, liquidity, market cap, and security
Learn how to clean datasets from missing values and duplicate values
Learn how to detect outliers in the dataset
Learn how to analyse and visualise daily and annual price volatility
Learn how to detect market trend and calculate moving average
Learn how to find correlation between price and volume using TensorFlow
Learn how to analyze market sentiment using Spacy
Learn how to forecast price using support vector regression
Screenshots
5532648
udemy ID
8/31/2023
course created date
9/3/2023
course indexed date
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