4+ year of data science experience.
2+ year of MLOps experience.
class SelfIntroduction:
def __init__(self):
self.programming_language = ['Python', 'Golang', 'Rust']
self.data_engineering = ['Mysql', 'Bigquery', 'MongoDB',
'Cloud-Storage', 'PostgreSQL']
self.feature_store = ['VertexAi-Features', 'Pipeline']
self.data_science = ['Python', 'Scikit-Learn', 'Tensorflow',
'Pytorch', 'Gensim', 'Opencv', 'Librosa',
'Gephi', 'TigerGraph']
self.mlops = ['Seldon-Core', 'VertexAi-Deploy', 'Kubernetes',
'Docker', 'Helm', 'Istio', 'Terraform', 'Kubectl',
'Flask', 'Cloud-Build', 'Google-Cloud-Platform']
self.business = ['PPT', 'Excel', 'Chart-of-numbers', 'Highcharts', 'HTML']
def complete_process(self):
# 1.Processing Data and Saving Features to feature store
self.data_engineering_function()
# 2.Query feature data from feature store
self.feature_store_function()
# 3.Use features to train the model
self.data_science_function()
# 4.Deployment Model
self.mlops_function()
# 5.Business Value Description
self.business_function()
def data_engineering_function(self):
'''
Read the data and process it into model features,
and then save it to the feature store.
exp:
Data -> pipline -> Feature -> Feature store
'''
print(f"1.Data engineering, tool: {self.data_engineering}.")
def feature_store_function(self):
'''
It is used to save the feature data of the model,
which can improve the feature utilization and version management.
exp:
1. Feature set version and key -> Feature
2. Feature key and time stamp -> Feature
3. Feature description and time stamp -> Feature
'''
print(f"2.Feature store, tool: {self.feature_store}.")
def data_science_function(self):
'''
It is used to explore the value of data
and transform mature results into models.
Finally, save the model to the model registry.
exp:
Feature -> Training model -> model
'''
print(f"3.Data science, tool: {self.data_science}.")
def mlops_function(self):
'''
It is used for model deployment (model API), monitoring and evaluation.
Developing and deployment commercial API.
exp:
model -> API -> model evaluation -> business api -> business evaluation
'''
print(f"4.Mlops, tool: {self.mlops}.")
def business_function(self):
'''
It is used for the evaluation of business value(make money).
exp:
business evaluation -> boss
'''
print(f"5.Business, tool: {self.business}.")