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Time Series Analysis and Forecasting Using Python in 2023

Name: Time Series Analysis and Forecasting Using Python in 2023
Price: 19.99 USD
Availability: InStock

About this course

Is this one of your needs?  Then course is for you Forecasting Online Users ?Forecasting Traffic ?Forecasting the expected performance of their loan portfolio?Forecasting real-estate properties?Forecasting User Spending Habits ?If there is some time dependency, then you know it - the answer is: time series analysis.Welcome to the best online resource for learning how to use the Python programming Language for Time Series Analysis!We'll start off with the basics by teaching you how to work with and manipulate data using the NumPy and Pandas libraries with Python. Then we'll begin to learn about the statsmodels library and its powerful built in Time Series Analysis Tools. Including learning about Error-Trend-Seasonality decomposition and basic Holt-Winters methods.We'll talk about creating AutoCorrelation and Partial AutoCorrelation charts and using them in conjunction with powerful ARIMA based models, including Seasonal ARIMA models and SARIMAX to include Exogenous data points.Then we'll learn about state of the art Deep Learning techniques with Recurrent Neural Networks that use deep learning to forecast future data points.This course will teach you the practical skills that would allow you to land a job as a quantitative finance analyst, a data analyst or a data scientist.In no time, you will acquire the fundamental skills that will enable you to perform complicated time series analysis directly applicable in practice. We take the most prominent tools and implement them through Python – the most popular programming language right now. With that in mind…With these tools we will master the most widely used models out there:· AR (autoregressive model)· MA (moving-average model)· ARMA (au

69/100

CourseAsk score

What the provider tells you: 45/45
Who stands behind it: 8/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

data manipulation using NumPy and Pandas
understanding time series analysis with statsmodels
creating AutoCorrelation and Partial AutoCorrelation charts
building ARIMA and Seasonal ARIMA models
implementing deep learning techniques for forecasting

Course objectives

to teach practical skills for time series analysis
to enable students to apply statistical models and machine learning techniques in forecasting
to prepare students for roles as quantitative finance analysts, data analysts, or data scientists

Machine Learning Data Analysis #deep learning #python #pandas #statsmodels #quantitative analysis #numpy #data science #forecasting #arima #recurrent neural networks #time series

$19.99

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