Q: How to apply machine learning to a csv file to predict future values I'm curious about ML and I wonder if some of you guys could help me getting started.
I have a dataset in a csv format like this:




Date
First
Second
Third




2022-12-30
5402
8694
8648


2022-12-29
3804
8529
6690


2022-12-28
3192
2779
2166




I want to predict first, second, and third values in the future time e.g. 2022-12-31.
What kind of algorithm is suitable to do this job? How do I have to implement this in my Jupyter notebook? Any example and/or reference of this problem will be so helpful to me. This is for predicting a 4-digit lottery game.
I have let panda to read my csv file and set it to a variable named "dataset"
import pandas as pd
import numpy as np
from sklearn.tree import DecisionTreeClassifier
from sklearn.model_selection import train_test_split

dataset=pd.read_csv("C:/Users/Administrator/Desktop/data.csv")

dataset['Date'] = pd.to_datetime(dataset.Date)


A: Here you are predicting the trend of the random winning number so linear regression would be the ideal choice for this.
