ikanez

# Sebastian Raschka 09/24/2022
# Create a new conda environment and packages
#   conda create -n whisper python=3.9
#   conda activate whisper
#   conda install mlxtend -c conda-forge

# Install ffmpeg
# macOS & homebrew
#   brew install ffmpeg
# Ubuntu

ikanez

def get_skills_context(resume):
    
    response = openai.Completion.create(
    engine="davinci",
    prompt="""This is a resume parser that extracts skills context from resume.
      
                resume: {resume1}
                parsed_contextual_skills: {extract1}
                
                ###

ikanez

resume_1 = """
  QUALIFICATIONS
  Highly motivated, customer focused professional with extensive experience in key client development and
  retention. Skilled in creating and growing solid customer relationships, needs analysis, and account activity
  tracking.
  EXPERIENCE
  EXPERIAN CORP 1998-2007
  Account Manager – Costa Mesa / Sacramento, CA 2002-2007
  Primary customer contact for the nation's largest collector and provider of real estate focused public record data.
  Industries serviced: Lending, Title, Investor and Government. Territory – AL, LA, MS, OK, TX

ikanez

# based on job classification on jobstreet.com
job_classification = [
        "accounting/finance",
        "admin/human resources",
        "sales/marketing",
        "arts/media/communications",
        "services",
        "hotel/restaurant",
        "education/training",
        "computer/IT",

ikanez

def call_openapi(title, desc):
    response = openai.Completion.create(
      engine="davinci",
      prompt="""This is a job specialization classifier
      
                Job title: Account Executive
                Job description: Handle full set of accounts.\n
                                Familiar with Income Tax filing.\n
                                Maintain daily cash flow and reporting.\n
                                Prepare monthly and annual financial reports.\n

ikanez

def call_openapi(question):
    response = openai.Completion.create(
      engine="davinci",
      prompt="""
        This is a banking expert.

        Q: What is interest rate?
        A: The interest rate is the amount a lender charges for the use of assets expressed as a percentage of the principal.

        Q: What is PD?

ikanez

from datetime import timedelta
num_window = 10

def last_day_of_month(any_day):
    next_month = any_day.replace(day=28) + timedelta(days=4)  # this will never fail
    return next_month - timedelta(days=next_month.day)


with mlflow.start_run(run_name='sarima_backtest'):
    t1 = pd.to_datetime('2017-01-31')

ikanez

# Initial approximation of parameters
Qs = range(0, 2)
qs = range(0, 3)
Ps = range(0, 3)
ps = range(0, 3)
D=1
d=1
parameters = product(ps, qs, Ps, Qs)
parameters_list = list(parameters)
len(parameters_list)

ikanez

import os
import mlflow
import mlflow.sklearn
# Set the experiment name to an experiment 
mlflow.set_experiment("/Shared/experiments/cryptocurrency/analysis-forecasting-1")

ikanez

for param in parameters_list:
    # start mlflow run
    with mlflow.start_run(run_name='arima_param'):
    
        # log parameters
        mlflow.log_param('param-qs', param[0])
        mlflow.log_param('param-ps', param[1])

        try:
            model = SARIMAX(btc_month.close_box, order=(param[0], d, param[1])).fit(disp=-1)