Portfolio of
Krisdan Kalinisan
Here are all things I got up to during my course (dsi-anz-dsifxr01) with General Assembly.
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All work is genuine and candid and reflects my abilities and organisation skills as at the day of submission
Project 1
Python-Initiation Coding Challenges
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Series of fun and challenging-at-the-time coding exercises that would warm anyone newcomer up for the half-year course ahead
Principals learnt
Python Lists
Python For-Loops
How to juggle full-time work and G.A.
Link to:
GitHub Repository:
https://github.com/krisdank/proj1-dsi-anz-dsifxr01
Project 2
The data behind the story 'How Baby Boomers get High'
Fun EDA exercise on two datasets: USA’s SAT scores for data behind the story ‘How Baby Boomers Get High’
My Python-Age on Due-Date: 43 days
Principals learnt
Python iteration control functions
Python types, lists, dictionaries
Python list comprehensions
Python functions
Pandas Dataframes
Data cleaning
Python Data Structures
Pandas Grouping
EDA visualization
Statistics hypothesis testing ttest & pvalues
EDA basic EDA walkthrough
Bootstrapping
Pandas Dataframe manipulation
Pandas long/wide/pivot/melt
Link to:
GitHub Repository:
https://github.com/krisdank/proj2-dsi-anz-dsifxr01
Project 3
Ames Housing Price Prediction
An immersive project tasked with predicting house prices from the well-used Ames Housing Dataset
My Python-Age on Due-Date: 92 days
Principals learnt
Model Selection
Regression
Classification
Prediction
Train-Test-Split
Linear regression
Feature scaling
Regression regularization
Logistic regression
Optimization feature selection
Link to:
GitHub Repository:
https://github.com/krisdank/proj3-dsi-anz-dsifxr01Original Dataset:
https://www.kaggle.com/tunguz/drug-use-by-age
Project 4
Webscraping seek.com
Webscraping project, automating job hunting
My Python-Age on Due-Date: 155 days
Principals learnt
Spyder
Webscraping
Natural Language Processing
Vectorizing
Link to:
GitHub Repository:
https://github.com/krisdank/proj4-dsi-anz-dsifxr01
Project 5
Dashboard Design
Our self-selected project: Create a dashboard for visualising the relationship between birth-order and personality traits
My Python-Age on Due-Date: 185 days
Learnt
Tableau
Principal Component Analysis (PCA)
Preprocessing, feature scaling
Cross validation train test
Logistic regression
Optimization feature selection
Optimization gridsearch hyperparameters
Link to:
