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Update README.md

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@@ -18,21 +18,23 @@ Change csv file path and run **"RECOMMENDATION MODEL"** part in **Job_Recommenda
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  ### Test recommeded system
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  In **TEST RECOMMENDED SYSTEM** part of **Job_Recommendation_System.ipynb** notebook, change **input_hard_skills, input_soft_skills, input_major** and run code to receive result
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- ## Add the get started code
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- ### Get started code
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  ```
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  import pickle
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  import pandas as pd
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- with open('recommendation_model.pkl', 'rb') as file:
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- tfidf_vectorizer_skills, tfidf_vectorizer_majors, companies_skills_vec, companies_majors_vec = pickle.load(file)
 
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- input_hard_skills = "Python, Java, Finance, Excel"
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- input_soft_skills = "Communication, Teamwork"
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- input_major = ""
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- jobs_data = pd.read_csv("jobs_data.csv")
 
 
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- recommended_jobs = recommend_jobs_for_input_skills(input_hard_skills, input_soft_skills, input_major, jobs_data, 'recommendation_model.pkl')
 
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  print("Recommended Jobs based on input skills and major:")
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  print(recommended_jobs)
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- ```
 
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  ### Test recommeded system
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  In **TEST RECOMMENDED SYSTEM** part of **Job_Recommendation_System.ipynb** notebook, change **input_hard_skills, input_soft_skills, input_major** and run code to receive result
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  ```
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  import pickle
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  import pandas as pd
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+ # Load the model
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+ with open('recommendation_pipeline.pkl', 'rb') as file:
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+ recommendation_pipeline = pickle.load(file)
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+ # Example input
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+ input_data = pd.DataFrame({
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+ 'final_hard_skill': ["Python, Java, Finance, Excel"],
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+ 'final_soft_skill': ["Communication, Teamwork"],
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+ 'candidate_field': [""]
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+ })
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+ # Make recommendations
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+ recommended_jobs = recommendation_pipeline.transform(input_data)
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  print("Recommended Jobs based on input skills and major:")
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  print(recommended_jobs)
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+ ```