tiffanysn / general_learning Goto Github PK

• add titanic data

• TCA model

• watch YT: implementation

• back-testing, scenario test @couyang24

• Jenkin
  watch YT : setup, unit test
  pytest

• SQL
  more practice on Partition by, Join( explain the differences)
  ETL, design, structure @couyang24

• Shiny @couyang24
  Streamlit, python(seaborn, plotly)

• knowledge
  object, pipline, ensemble model, machine learning, deep learning, xgboost, linear regression

• go through CV
  build project

• Stock price app

• Sales data app

• Seaborn, plotly

• groupby, pivot, str extract

• SQL join

• Jenkins

• ML knowledge

• finish 3 LeetCode Qs

Please provide estimated time to complete.
https://github.com/sqlfluff/sqlfluff

• t- test

• Control store 95th &5th percentile

• plot

• U practice in Python

• SQL datacamp

• Survival rate by different segments (sex, age and p-class etc)
• Biggest survived group
• Imputation missing values

• Linear Regression
  stats quest

• General Qs
  introduction / why us / describe a day / career goal /

• xgboost
  GBM / Decision Tree

• Object-Oriented
  Coursera Python 3

• SQL
  join / partition by

• Streamlit
  geographic

• Jenkins
  unit test

• Find number of rows and columns
• FInd what is the target variable
• Find data type of the feature variables
• Is there any missing value and how should be impute the values (potential solutions)
• Visualize the distribution of some features/ target
• Find the connection between features and target

• use sklearn to make ml model
• based on the model of your choice identify the feature importance
• submit the result to kaggle to check performance

• data exploration
• visualization
• get insights
• give suggestion

• generate additional features using featuretools

• Scale pre-trial control customers to match pre-trial trial store customers
• apply the scaling factor to control store customer counts
• calculate the percentage difference between scaled control store customers and trial customers
• standard deviation
• Control store 5th & 95th percentile
• plot

• finish 3 leetcode easy Qs

• SQL DATACAMP

• Create function to cal the correlation

• Standardise the magnitude distance

• Create a combined score composed of correlation and magnitude

• Select the most appropriate control store

• Visual checks on trends

• Complete Part 1: Select control store

• Apply PC role

• Datacamp- SQL DB

• Apply the scaling factor

• Calculate the percentage difference between scaled control sales and trial sales

• REPORTING IN SQL & REAL WORLD PROBLEM

• COURSERA Python/ WEEK 1