Maybe you’re just trying to get a better sales forecast for your small business!
Time series forecasting can help!
In this video you’ll learn how to QUICKLY use time series forecasting to produce a forecast. In just a couple of minutes you’ll be able to preprocess your dataset using Pandas and forecast over a number of time periods using Facebook Prophet.
In this video you’ll learn how to:
1. Preparing Data for Time Series FC
2. Training Prophet Time Series Models
3. Making forecast predictions
GET THE CODE!
Kite is a free AI-powered coding assistant that will help you code faster and smarter. The Kite plugin integrates with all the top editors and IDEs to give you smart completions and documentation while you’re typing. I’ve been using Kite. Love it!
Learn more: https://www.kite.com/get-kite/?utm_medium=referral&utm_source=youtube&utm_campaign=codeemporium&utm_content=description-only
1:51 Defining Problem
2:50 Understanding the Data
3:18 Analyzing Data (Trend, Seasonality)
4:40 Traditional Timeseries Forecasting (ARIMA, Prophet)
6:01 Univariate & Multivariate Time series
8:15 Time series with Machine Learning
9:02 Types of Time series models
11:05 Machine Learning Vs. Traditional Time Series
 Math behind Facebook prophet: https://medium.com/future-vision/the-math-of-prophet-46864fa9c55a
 Traditional time series analysis step by step: https://www.kaggle.com/freespirit08/time-series-for-beginners-with-arima
 Dealing with time series data: https://online.stat.psu.edu/stat510/lesson/1
 Catboost is slick : https://catboost.ai/docs/concepts/tutorials.html
Is it right or wrong for Christians to invest in the stock market? Investing in the stock market is a part of investing in a functioning economy and, if done right and for the right reasons, can be an incredible blessing. Learn more in today’s Little Lesson!
For more Bible teaching, check out my YouTube Channel. Be sure to subscribe!
You can also read a blog post based on this video at my website:
This video is part of Time Series playlist here – https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJd6GrQvhAtpBK
One major challenge with time series in real world is dealing with multiple time series, Be it retailers who have millions of product and every product having different sales cycle or manufacturing industry dealing with hundreds of machinery. In such cases we need systems and solution that can help distribute time series model building across distributed nodes to enable high parallelism. In this video we will see how we can use facebook prophet to model and Apache Spark to distribute across multiple nodes