anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

auditing_fraud_detection

Implementing resampling methods to address imbalanced data; Trained Random Forest, XGBoost and neural network, and conducted stepwise feature selection

bank_deposit_prediction_by_mlp

Structured Neural Network with TensorFlow keras to predict the result of a telemarketing phone calls to sell long-term deposits as a valuable tool to support client selection decisions for bank campaign managers, reaching 89.61% AUC

beyond-leetcode-sql

Analysis of SQL Leetcode and classic interview questions. Common pitfalls, anti-patterns and handy tricks are discussed. Sample databases are provided.

credit_card_fraud_detection

Performed data analysis on 284,000 credit card transactions; applied resampling method SMOTE to handle imbalanced data; Trained Machine Learning models including Lasso, Random Forest and GBM to identify fraudulence; Measured the model performance by PR AUC score, the XGBoost classifier got the highest F1 score of 0.8778

ecommerce_consumer_behavior_and_purchase_intention

Conducted data wrangling on 200K+ records of customer demographic information and online behavior data；Built classifiers with logistic regression and random forest to predict customer activities, achieving 81% accuracy；Provided compelling data stories and recommendations to reduce bounce rate, improve conversion rate and click-through rates

introtostatisticallearningr-

Work on Introduction to Statistical Learning

leetcode_solutions

144 efficient solutions to LeetCode problems

lendingclub

mapreduce_customer_spending

Use Python to create a MapReduce program to determine the Total Amount spent by Customer, and sort the Total Amount spent by Customer (from the Customer who spent the least to the Customer who spent the most),

mapreduce_ecommerce

Using Mapreduce to analyst customer reviews and finding popular product

ml_project_tempalte

py_ds_ml

python_leetcode

Python_Leetcode

r_ml_islr

Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR)

sql_leetcode_database

My solutions (MySQL and TSQL) with explanation to Leetcode Database questions.

sql_notebook

standford-machine-learning

statistics-for-data-scientists

Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"

walmart_store_sales_forecasting

Built sales forecast model to help Walmart better segment customers to personalize the service and advertising; Performed exploratory data analysis and preprocessed 650K+ rows of raw data, dealing with multi-class imbalance, categorical feature encoding and feature scaling; achieved 68% accuracy and 0.70 F1-score using random forest