[Kaggle Study Curriculum] 캐글 스터디 커리큘럼

👍 최근 가장 많은 관심을 받고 있는 분야는 AI/데이터분석 직무일 것이다.
요즘 다수의 기업에서 데이터분석 직무가 새로 생기고 있거나,

예전에 비해 직무에 대한 전문성을 많이 요구하고 있다.

 

👩‍💻 21년 상반기 취업을 준비하면서 대부분의 데이터 직무에서 코딩 테스트 시험이 추가된 것을 볼 수 있었다.

그 중 KB국민은행의 코딩 테스트에 합격을 했었는데, 일반 코딩과 SQL 문제가 각각 2개씩 나왔었다.

 

확실히 예전에 비해 코딩에 대한 직무적 역량이 요구 됨을 느낄 수 있었다.

하반기 취업에서는 일반 코딩 테스트 와 데이터 분석 코딩 테스트 를 준비할 계획이다.

 

🗓 현재 진행하고 있는 데이터 분석 스터디에서는 아래의 커리큘럼을 참고하고 있다.

그럼, 커리큘럼에 맞춰 시작해보자.

 

 

 

스터디 커리큘럼 

📍Binary classification : Tabular data 

1st level. Titanic: Machine Learning from Disaster

• 타이타닉 튜토리얼 1 - Exploratory data analysis, visualization, machine learning
• EDA To Prediction(DieTanic)
• Titanic Top 4% with ensemble modeling
• Introduction to Ensembling/Stacking in Python

 

2nd level. Porto Seguro’s Safe Driver Prediction

• Data Preparation & Exploration
• Interactive Porto Insights - A Plot.ly Tutorial
• XGBoost CV (LB .284)
• Porto Seguro Exploratory Analysis and Prediction

 

3rd level. Home Credit Default Risk

• Introduction: Home Credit Default Risk Competition
• Introduction to Manual Feature Engineering
• Stacking Test-Sklearn, XGBoost, CatBoost, LightGBM
• LightGBM 7th place solution

 

📍Multi-class classification : Tabular data 

1st level. Costa Rican Household Poverty Level Prediction

• A Complete Introduction and Walkthrough
• 3250feats->532 feats using shap[LB: 0.436]
• XGBoost

 

📍Binary classification : Image classification 

1st level. Statoil/C-CORE Iceberg Classifier Challenge

• Keras Model for Beginners (0.210 on LB)+EDA+R&D
• Transfer Learning with VGG-16 CNN+AUG LB 0.1712
• Submarineering.EVEN BETTER PUBLIC SCORE until now.
• Keras+TF LB 0.18

 

📍Multi-class classification : Image classification 

1st level. TensorFlow Speech Recognition Challenge

• Speech representation and data exploration
• Light-Weight CNN LB 0.74
• WavCeption V1: a 1-D Inception approach (LB 0.76)

 

📍Regression : Tabular data 

1st level. New York City Taxi Trip Duration

• Dynamics of New York city - Animation
• EDA + Baseline Model
• Beat the benchmark!

 

2nd level. Zillow Prize: Zillow’s Home Value Prediction (Zestimate)

• Simple Exploration Notebook - Zillow Prize
• Simple XGBoost Starter (~0.0655)
• Zillow EDA On Missing Values & Multicollinearity
• XGBoost, LightGBM, and OLS and NN

 

📍Object segmentation : Deep learning

1st level. 2018 Data Science Bowl

• Teaching notebook for total imaging newbies
• Keras U-Net starter - LB 0.277
• Nuclei Overview to Submission

 

📍Natural language processing : classification, regression

1st level. Spooky Author Identification

• Spooky NLP and Topic Modelling tutorial
• Approaching (Almost) Any NLP Problem on Kaggle
• Simple Feature Engg Notebook - Spooky Author

 

2nd level. Mercari Price Suggestion Challenge

• Mercari Interactive EDA + Topic Modelling
• A simple nn solution with Keras (~0.48611 PL)
• Ridge (LB 0.41943)
• LGB and FM [18th Place - 0.40604]

 

3rd level. Toxic Comment Classification Challenge

• [For Beginners] Tackling Toxic Using Keras
• Stop the S@#$ - Toxic Comments EDA
• Logistic regression with words and char n-grams
• Classifying multi-label comments (0.9741 lb)

 

📍Other dataset : anomaly detection, visualization

1st level. Credit Card Fraud Detection

• In depth skewed data classif. (93% recall acc now)
• Anomaly Detection - Credit Card Fraud Analysis
• Semi-Supervised Anomaly Detection Survey

 

2nd level. Kaggle Machine Learning & Data Science Survey 2017

• Novice to Grandmaster
• What do Kagglers say about Data Science ?
• PLOTLY TUTORIAL - 1

 

 

커리큘럼 출처: https://kaggle-kr.tistory.com/32?fbclid=IwAR1k1ZZhbep5L5yngqRpglRkrap49K-2tCRYoqP1Yx-AlorfIMOOLxcIgfQ