Python for Pandas, Statsmodels, ARIMA, SARIMAX, Deep Learning, LSTM, and Future Forecasting into future in the Time Series Analysis and Forecasting with Python udemy course
What you'll learn
- Basic Packages, NumPy, Pandas & Matplotlib
- Time Series with Pandas (Creating Date Time index, Resampling, …)
- Analyzing Time Series Data Using Statsmodels Package
- The Concept of ARIMA and SARIMAX method and How to Forecast into the Future Using Them
- The Concept of Deep Learning from A-Z
- Forecast into the Future Using LSTM Model for Single Variant
- Forecast into the Future Using LSTM Model for Multi Variant
- General and Basic Python Skills
The “Time Series Analysis and Forecasting with Python” course is the most comprehensive resource for understanding time series principles and forecasting into the future.
The most well-known approaches, such as statistical methods (ARIMA and SARIMAX) and Deep Learning Method (LSTM), are thoroughly presented in this Time Series Analysis and Forecasting with Python course. Moreover, numerous Real World applications are written in Python and have been taught line by line!
You've come to the right spot if you're a researcher, a student, a programmer, or a data science enthusiast looking for a Time Series Analysis and Forecasting with Python course that will teach you all you need to know about time series and prediction from A to Z. Take a look at what you'll study in this course:
- Basic libraries (NumPy, Pandas, Matplotlib)
- How to use Pandas library to create DateTime index and how to set that as your Dataset index
- What are statistical models?
- How to forecast into future using the ARIMA model?
- How to capture the seasonality using the SARIMAX model?
- How to use endogenous variables and predict into future?
- What is Deep Learning (Very Basic Concepts)
- All about Artificial and Recurrent Neural Network!
- How the LSTM method Works!
- How to develop an LSTM model with a single variate?
- How to develop an LSTM model using multiple variables (Multivariate)
As I previously stated, we attempted to show how to create an LSTM model when you have many predictors (variables) for the first time, and how to utilize it for a variety of applications while also using the source code for your project!
Everyone is welcome to take this Time Series Analysis and Forecasting with Python course! Everyone, yeah! Anyone wants to learn time-series and future forecasting using statistics and artificial intelligence, regardless of their experience! I show you how to write and create your model line by line, even if you aren't a coder!
Check out my other Time Series Analysis and Forecasting with Python courses if you want to learn the fundamentals of Machine Learning in Python as well!
Who this course is for:
- Data Science Enthusiast
- Beginner Programmers
- Python Developers
- Recheachers who like to forecast into future
- Data Analysts
- Anyone who is interested in Time Series and Future Forecasting
Created by Navid Shirzadi
Last updated 8/2021
Size: 3.9 GB