Time Series Forecasting Using Machine Learning| Python

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In this video i show how you can use machine learning(ML) technqiues to make time series predictions and forecasting.
You can convert time series data into supervised learning problem by shifting the dataset. In this video I use linear regression and random forest machine learning models to make time series forecasting in python.

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Great video, thanks. However, what about the future forecasts? Like for x_test we have fed the lag values of the dependent variable, but those aren't available with us. Suppose we have the data till feb 2022, and want to forecast for next 3 months, we don't have the x_test ie lag values available for next 3 months right? I think this is where rolling time window or something like walk forward validation is needed

chaitrabellur

Brother,
only training and testing done here, what about the future forecast? As we are interested in future predictions.

shubhamnehete

Many thanks for your good sharing. May I know if it would help to improve the prediction results by making the data stationary before going ahead with the time series forecasting using ML? Thanks.

darellelee

Great job with the videos. I've learned so much here!!

raheempaxton

Why not do the autocorrelation first to determine the significant lag? Since you put the lag shift directly, your basic reasoning for the model fit becomes weak.

concretemathematics

Hi, how can i perform out of sample forecasts using your model?

wjvesrd

Hey man, great pointers on how to convert regular csv into time series data. However, I don't think you should really call a linear model machine learning. If you had a massive dataset it would be way to time consuming to make a new column for each month back.

jamesbailey

Hello nachiket what about future prediction? how can i know next month prediction?

kshitijrandive

This is a great video. But how do you predict the value of sales for the next year?

ivzuohi

Nice explaination.
Can you try multivariate using prophet model

asura

thank you for getting me through university.

LauraPeculiar

Nice work bro..please answer this question.I understood the whole process of taking the previous 3 values for every datapoint as input features.But shouldnt a Linear regression model give a single straight line output.I was asked this in interview and couldnt answer properly.Kindly give your answer on this.

divyanshuchaudhari

You should use a rolling/expanding time window for train/test split.

jcnvlju

Like you do for ARIMA model, should you make the time series data stationary even when you use machine learning models?

sehyunko

do we need to have regular intervals of timeseries for prediction?

what if we have to predict next days sale, using previous_1 and previous_2 days, and we dont have previous_1 day value for some rows?

if we need regular intervals of timeseries for prediction, how to get previous_1 in this case?

rohandevaki

also how to predict the next one month values? using inferencing? or next 10 month values using inferencing?

rohandevaki

My friend wanted to do B Tech in AI/ML after diploma, can you suggest the carrer path for the same ?

bhambhomoto

I'm enchanted by this content. I read a book with similar content, and I was truly enchanted. "The Art of Meaningful Relationships in the 21st Century" by Leo Flint

Bill

How come we are not checking the stationarity before starting with the model? Or forecasting using machine learning somehow automatically takes care of that? I'm kinda confused

HaiderAli-ppgo

hi mr. nachi. if i have data that use "year", what do I change to the code?

tvirfcx

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