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Time Series Analysis in Python | Time Series Forecasting | Data Science with Python | Edureka
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This Edureka Video on Time Series Analysis n Python will give you all the information you need to do Time Series Analysis and Forecasting in Python. Below are the topics covered in this tutorial:
1. Why Time Series?
2. What is Time Series?
3. Components of Time Series
4. When not to use Time Series
5. What is Stationarity?
6. ARIMA Model
7. Demo: Forecast Future
Subscribe to our channel to get video updates. Hit the subscribe button above.
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)
#timeseries #timeseriespython #machinelearningalgorithms
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About the Course
Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.
During our Python Certification Training, our instructors will help you to:
1. Master the basic and advanced concepts of Python
2. Gain insight into the 'Roles' played by a Machine Learning Engineer
3. Automate data analysis using python
4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
6. Explain Time Series and it’s related concepts
7. Perform Text Mining and Sentimental analysis
8. Gain expertise to handle business in future, living the present
9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
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Why learn Python?
Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.
1. Why Time Series?
2. What is Time Series?
3. Components of Time Series
4. When not to use Time Series
5. What is Stationarity?
6. ARIMA Model
7. Demo: Forecast Future
Subscribe to our channel to get video updates. Hit the subscribe button above.
(450+ Hrs || 9 Months || 20+ Projects & 100+ Case studies)
#timeseries #timeseriespython #machinelearningalgorithms
- - - - - - - - - - - - - - - - -
About the Course
Edureka’s Course on Python helps you gain expertise in various machine learning algorithms such as regression, clustering, decision trees, random forest, Naïve Bayes and Q-Learning. Throughout the Python Certification Course, you’ll be solving real life case studies on Media, Healthcare, Social Media, Aviation, HR.
During our Python Certification Training, our instructors will help you to:
1. Master the basic and advanced concepts of Python
2. Gain insight into the 'Roles' played by a Machine Learning Engineer
3. Automate data analysis using python
4. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
5. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
6. Explain Time Series and it’s related concepts
7. Perform Text Mining and Sentimental analysis
8. Gain expertise to handle business in future, living the present
9. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience
- - - - - - - - - - - - - - - - - - -
Why learn Python?
Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.
Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license.
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain.
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