Dataman Learning Paths— Build Your Skills, Drive Your Career
Dataman has contributed more than 90 articles in data science practices and applications. These articles are used in my lectures. Many of the articles provide codes or applications for you to follow through. Depending on your familiarity on certain topics, you may spend 20 minutes to an hour — that’s the beauty of the learning path. To help you manage the learning in a short period of time, this article organizes them into several learning paths. Some of the articles cover two or more topics. I still put each of them into one topic so as not to show you a duplicated list. Dataman also wants to thank you for your support. I will continue to write good articles. So bookmark this post and read on!
On Feature Engineering
- Feature Engineering for Healthcare Fraud Detection
- Feature Engineering for Credit Card Fraud Detection
- A Data Scientist’s Toolkit to Encode Categorical Variables to Numeric
- Avoid These Deadly Modeling Mistakes that May Cost You a Career
- Are you Bilingual? Be Fluent in R and Python
- Algorithmic Trading with Technical Indicators in R
- Julia Is Easy to Learn — Fluent in Python, Julia, and R
On Economic Analysis
- Plot the U.S. Economic Leading Indicator PMI with Plotly
- How Do We Pay for the Coronavirus Stimulus Package?
- Let’s Talk About the Taylor Rule for Monetary Policy
On Data Visualization
- Create Beautiful Geomaps with Plotly
- Powerful Plots with Plotly
- Pandas-Bokeh to Make Stunning Interactive Plots Easy
- Use Seaborn to Do Beautiful Plots Easy
On Model Interpretability
- Explain Your Model with the SHAP Values
- Explain Any Models with the SHAP Values — Use the KernelExplainer
- The SHAP with More Elegant Charts” for the recent development
- “Creating Waterfall Plots for the SHAP Values for All Models”.
- Explain Your Model with LIME
- Explain Your Model with Microsoft’s InterpretML
- Business Forecasting with Facebook’s “Prophet”
- An Explanation for eXplainable AI
On Modeling Techniques
- My Lecture Notes on Random Forest, Gradient Boosting, and Regularization
- Dimension Reduction Techniques with Python
- How to determine the best model?
- Using Over-Sampling Techniques for Extremely Imbalanced Data
- Using Under-Sampling Techniques for Extremely Imbalanced Data
- Why Can’t I Just Use the ROC Curve?
- Machine Learning Must Know — From Raw to Training Data
- A Tutorial on Quantile Regression, Quantile Random Forests, and Quantile GBM
- Start Using Google Colab Free GPU
- Building An Agent-Based Model with Python for Ant Foraging
On Differential Privacy
On Deep Learning & Image Recognition
- What Is Image Recognition?
- Convolutional Autoencoders for Image Noise Reduction
- The Applications of Image Recognition in Insurance
- Deep Learning with PyTorch Is Not Torturing
- Explaining Deep Learning in a Regression-Friendly Way
- A Technical Guide on RNN/LSTM/GRU for Stock Price Prediction
On Fraud Detection
- Anomaly Detection with Autoencoders Made Easy
- Use the Isolated Forest with PyOD
- “Stock Market Anomalies” and “Stock Market Anomaly Detection” Are Two Different Things
- The Growth of Fraud Risks
On Time Series Anomaly Detection
- Algorithmic Trading with Technical Indicators in R
- Anomaly Detection for Time Series
- Kalman Filter Explained!
On Natural Language Processing
- Looking into Natural Language Processing (NLP)
- NLP for EHR? — Natural Language Processing for Electronic Health Records
On Insurance Industries & Innovation
- A Primer to Auto Insurance Pricing for Data Scientists
- Telematics in Auto Insurance
- The Applications of Image Recognition in Insurance
- Climate Change and Insurance Management
- What Is General Liability Insurance?
On Healthcare
- NLP for EHR? — Natural Language Processing for Electronic Health Records
- Data Science Use Cases for Healthcare
- Cope with the Rising Costs of COPD
On Identifying Causality
- Design of Experiments for Your Change Management
- Machine Learning or Econometrics?
- Identify Causality by Regression Discontinuity
- Identify Causality by Difference in Differences
- Identify Causality by Fixed-Effects Models
On Storytelling
On Management
- Design the Right Job Functions to Develop Your Data Science Team
- Turn Data Science Into Competitive Edge
- Data Science Modeling Process & Six Consultative Roles
- 100 Business Quotes
- The Talk Track to Promote Your Data Science Projects
- Reinventing a Business Process
On Model Monitoring & Dashboard
- Monitor Your Machine Learning Model Performance
- Build an R Shiny Dashboard to Monitor Your Model Performance
- Build My Medium Dashboard with R Shiny
- Build the Tableau Storyline to Monitor Your Model Performance
- Building a Stock Market App with Python Streamlit in 20 Minutes
On Python Programming
