Description
Course Introduction to Time Series with Python 2023. Are you interested in the subject of time series? Then this course is right for you! A software engineer designed this course. With the experience and knowledge I have gained over the years, I can share my knowledge and help you learn complex theory, algorithms and coding libraries easily. I will introduce you to the concept of time series and how to apply machine learning techniques to time series. With each tutorial, you’ll develop new skills and improve your understanding of this challenging yet rewarding subfield of machine learning. This course is fun and exciting, but at the same time, we take you deep into time series with concepts and exercises to help you understand what time series are and how to implement them. During the all-new version of the course, we cover many tools and technologies, including:
- Pandas
- Matplotlib
- learned
- State models
- Scipy
- Prophet
- born in the sea
- Z score
- Turkish method
- silver
- Red and white sound
- Rupture
- XGBOOST
- Alibi_identification
- STL parsing
- Convergence
- autocorrelation
- Spectral residual
- MaxNLocator
- Winsorization
- February order
- Additive seasonality
- Multiplicative season
- Univariate assignment
- Multivariate imputation
- Interpolation
- Forward padding and backward padding
- Moving Average
- Autoregressive moving average models
- Fourier analysis
- ARIMA model
In addition, the course is full of practical exercises based on real-life examples. So you will not only learn the theory, but you will also have the practical practice of making your own models. There are five major projects on health care problems and one small project on action. These projects are listed below:
- NYC taxi project
- Air passengers project
- Movie box office project.
- CO2 project
- Click on Project.
- Sales project.
- Beer production project
- Medical treatment project
- Divvy bike sharing app.
- Instagram.
- Sunspots
What you will learn in the Introduction to Time Series with Python 2023 course
-
State models
-
Red and white sound
-
Spectral residual
-
Additive seasonality
-
Univariate assignment
-
Multivariate imputation
-
Forward padding and backward padding
-
Moving Average
-
Autoregressive moving average models
This course is suitable for people who
- Anyone interested in machine learning.
- Students who have at least a high school background in mathematics and want to get started in machine learning, deep learning, and artificial intelligence.
- All people who are not very comfortable with coding but are interested in machine learning, deep learning, artificial intelligence and want to easily apply it to datasets.
- Any college student who wants to start a career in data science
- Anyone who wants to create added value for their business by using powerful tools of machine learning, artificial intelligence and deep learning. All people who want to work in an automotive company as a data engineer, machine learning, deep learning and artificial intelligence engineer.
- Anyone who wants to improve their knowledge in machine learning, deep learning and artificial intelligence
Details of the Introduction to Time Series with Python 2023 course
- Publisher: Udemy
- teacher: Hoang Quy La
- Training level: beginner to advanced
- Training duration: 17 hours and 16 minutes
- Number of courses: 77
Course topics Introduction to Time Series with Python 2023
Prerequisites for the Introduction to Time Series with Python 2023 course
- Basic python is required
- Basic machine learning knowledge is required
Course images
Sample video of the course
Installation guide
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download link
File(s) password: www.downloadly.ir
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