09-04-2023, 04:26 AM
Forecast Crypto Market with Time Series and Machine Learning
Learn how to forecast cryptocurrency market with Prophet model, time series decomposition, Random Forest, and XGBoost
New
Rating: 0.0 out of 5
(0 ratings)
932 students
3 hours on-demand video
4 downloadable resources
Description
Welcome to Forecasting Cryptocurrency Market with Prophet, Time Series and Machine Learning course. This is a comprehensive project based course where you will learn step by step on how to perform complex analysis and visualization on cryptocurrency market dataset. This course will be focusing mainly on forecasting cryptocurrency prices using three different forecasting models, those are Prophet, time series decomposition, and machine learning particularly we are going to be utilizing Random Forest and XGBoost. Regarding programming language, we are going to use Python alongside with several libraries like Pandas for performing data modeling, Numpy for performing complex calculations, Matplotlib for visualizing the data, and TensorFlow which is an open-source machine learning library used for building and training various deep learning models. Meanwhile, for the data source, we are going to download the crypto market dataset from Kaggle. In the introduction session, you will learn basic fundamentals of cryptocurrency market forecasting, such as getting to know the crypto market characteristics and forecasting models that will be used.
https://www.udemy.com/course/forecast-crypto-market-with-time-series-machine-learning/?couponCode=A86095CB5C91F04F4B91
Enjoy!
Learn how to forecast cryptocurrency market with Prophet model, time series decomposition, Random Forest, and XGBoost
New
Rating: 0.0 out of 5
(0 ratings)
932 students
3 hours on-demand video
4 downloadable resources
Description
Welcome to Forecasting Cryptocurrency Market with Prophet, Time Series and Machine Learning course. This is a comprehensive project based course where you will learn step by step on how to perform complex analysis and visualization on cryptocurrency market dataset. This course will be focusing mainly on forecasting cryptocurrency prices using three different forecasting models, those are Prophet, time series decomposition, and machine learning particularly we are going to be utilizing Random Forest and XGBoost. Regarding programming language, we are going to use Python alongside with several libraries like Pandas for performing data modeling, Numpy for performing complex calculations, Matplotlib for visualizing the data, and TensorFlow which is an open-source machine learning library used for building and training various deep learning models. Meanwhile, for the data source, we are going to download the crypto market dataset from Kaggle. In the introduction session, you will learn basic fundamentals of cryptocurrency market forecasting, such as getting to know the crypto market characteristics and forecasting models that will be used.
https://www.udemy.com/course/forecast-crypto-market-with-time-series-machine-learning/?couponCode=A86095CB5C91F04F4B91
Enjoy!