Register
Login
Resources
Docs Blog Datasets Glossary Case Studies Tutorials & Webinars
Product
Data Engine LLMs Platform Enterprise
Pricing Explore
Connect to our Discord channel

research.py 346 B

You have to be logged in to leave a comment. Sign In
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
  1. from mlProject.pipeline.prediction import PredictionPipeline
  2. import numpy as np
  3. state= 5
  4. numcol = 22
  5. yieldpercol = 22
  6. totalprod =5
  7. stocks =25
  8. prodvalue=22
  9. year=2022
  10. data = [state, numcol, yieldpercol, totalprod, stocks, prodvalue, year]
  11. data = np.array(data).reshape(1, 7)
  12. obj = PredictionPipeline()
  13. predict = obj.predict(data)
  14. print(predict)
Tip!

Press p or to see the previous file or, n or to see the next file

Comments

Loading...