Time Series with Python: How to Implement Time Series Analysis and Forecasting Using Python (Financial Data Analytics Using Python Book 2)

Price: $31.81
(as of Jan 22,2025 11:50:57 UTC – Details)

ASIN ‏ : ‎ B0861T6W53
Publication date ‏ : ‎ April 12, 2020
Language ‏ : ‎ English
File size ‏ : ‎ 14590 KB
Simultaneous device usage ‏ : ‎ Unlimited
Text-to-Speech ‏ : ‎ Enabled
Screen Reader ‏ : ‎ Supported
Enhanced typesetting ‏ : ‎ Enabled
X-Ray ‏ : ‎ Enabled
Word Wise ‏ : ‎ Not Enabled
Print length ‏ : ‎ 166 pages
Page numbers source ISBN ‏ : ‎ 1393147380

In this post, we will explore the world of time series analysis and forecasting using Python. Time series data is a sequence of data points collected at regular intervals over time. This type of data is commonly encountered in finance, economics, weather forecasting, and many other fields.

In our Financial Data Analytics Using Python Book 2, we will cover the following topics:

1. Introduction to time series analysis and forecasting
2. Preparing time series data for analysis
3. Exploratory data analysis of time series data
4. Time series decomposition
5. ARIMA modeling for time series forecasting
6. Seasonal ARIMA modeling
7. Prophet modeling for time series forecasting
8. Evaluating time series forecasting models
9. Forecasting future values of time series data

We will provide step-by-step instructions and code examples to help you implement time series analysis and forecasting using Python. By the end of this book, you will have the skills and knowledge to analyze and forecast time series data for financial applications.

Stay tuned for more updates on Financial Data Analytics Using Python Book 2 and unlock the power of time series analysis and forecasting with Python.
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