Final Report

SOC completed successfully 

ARIMA model is an amazing model that can be used to predict the future depending upon the past performance. 
It's application is limitless including the stock market and the financial standings of the sales and margins.
However, It needs to be accompanied with a seasonal change to make it useful. Mostly it should be used in a way with other information. 
Sometimes it can be misleading I

ARIMA Model background- https://www.machinelearningplus.com/time-series/arima-model-time-series-forecasting-python/
Seasonal ARIMA- https://www.machinelearningplus.com/time-series/arima-model-time-series-forecasting-python/
I read this apart from the notion page

Notion Page- https://hurricane-farm-a92.notion.site/Stock-Market-Prediction-ARIMA-MODEL-9490ec7017d64f87a0c62f537464fb3b

Major stuff learned-

1) Python was the only language that was required to be used.
    I saw the video provided by the mentor and solved the google collab provided(could not presevre either)
2) Numpy was learned in the initial days to get a feel of how python is actually the more useful language
    Followed mainlyu the video and tried a few commands to see the use
3) Pandas that was built on numpy was used for the databasing and effective operation on data. This is a powerfull library that is used in many places and applications
    Having tried video learning and seeing that it is faster to grasp content continued on it
4) EDA- Exploratory Data Analysis was a bit of a difficult topic to wrap the head around. I read a few more articles for the same to get a better grasp on it.
    The cruz of it being that we use python pandas functions associated with it and find some relation using the calculated stuff.
5) YFinance- it is a powerful library that helps us get a structured details about a particular stock so that it can be used in the operations
    It structures the data beautifully to ensure that it can be used properly.
6) ARIMA model- we used the research paper to get a good grasp on the arima model and the background was used from the article itself.
7) I tried many ways to grasp my head around the idea and then with the help of the mentor, I discovered Seasonal ARIMA model that produced the desired results

I would believe it to be a success as i got to learn the power of so many libraries. 
Altough, I did not save the file in which I ran the commands which were provided in the various videos.

I have uploaded the final assignment which uses the application of all the above stuff and is impossible to learn without putting in time.