Browsers are
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1. Understand Business
Problem & Create
Project Charter
2. Data Collection
a. Primary Data Sources
b. Secondary Data
Sources
CRISP-DM (Cross
Industry Standard
Process for Data
Mining)
Python Programming
1. Understand Business
Problem & Create
Project Charter
2. Data Collection
3. Data Cleansing /
Preparation / EDA /
Feature Engineering
a. Data Cleansing / Data
Preparation / Data
Munging / Data
Wrangling
b. Exploratory Data
Analysis / Descriptive
Statistics
4. Data Mining /
Machine Learning
5. Model Evalution
6. Model Deployment
R Programming
3. Data Cleansing /
Preparation / EDA /
Feature Engineering
a. Data Cleansing / Data
Preparation / Data
Munging / Data
Wrangling
b. Exploratory Data
Analysis / Descriptive
Statistics
4. Data Mining /
Machine Learning
Supervised Learning
Predictive Modelling
Unsupervised Learning
or Descriptive Model
Forecasting / Time
Series
R Packages
5. Model Evaluation
6. Model Deployment
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