Model Iteration Series: Validating Model Infra
The system and product side of concerns
2024
Model Iteration Series: Validating Model Research
The first line of defense to robust model iteration
Model Iteration Series: Intro
An overview of industry-level model iteration procedure
Testing in Machine Learning
A holistic approach to evaluate machine learning code
Prompt Engineering Whitebook
A copy of what I learned and gathered about prompting, both from online and from work
A good Python projecttemplate to use as starting point
A summary of many masterminds' projects style
Writing Quality Code for Machine Learning
Draft notes on proof-of-concept ML code, separation of concerns, configuration, legacy models, and type/documentation hygiene.
MLOps Post Training Considerations
An Overview of how to design a full-stack Deep Learning System
Understanding Distributed Training in Deep Learning
What's important in industry AND research, not taught in school???
Some Tricks in Real-world Machine Learning Engineering
Draft notes on feature engineering, notebook conversion, missing values, scaling, and categorical encoding.
Quantization in Deep Learning
A must-know technique to save your computation resources
DL Training: An in-depth discussion
Training can be hard a lot of time. But the bottlenecks vary
Fine-tuning in LLM
Draft notes on LoRA, prompt tuning, adapter tuning, RLHF, and DPO.
Starting your AI/ML Project: from research to engineering
Things you need to do before starting a real-world AI/ML engineering project
Testing Machine Learning Systems
Draft notes on software tests, model evaluation, and model behavior tests.
Deep Learning System Design - A Checklist (Part II)
An Overview of how to design a full-stack Deep Learning System
Deep Learning System Design - A Checklist (Part I)
An Overview of how to design a full-stack Deep Learning System
2023
Neural Network Applied: Optimizer Selection
Choose a good optimization strategy is as important as selecting the right model
Needle: High-performance DL System
A Deep Learning framework with customized GPU and CPU backend in C++ and Python
Motion Prediction with Guided Diffusion
Researched and developed a classifier-free guidance-based latent diffusion model for autonomous vehicle motion forecasting using UNet and Transformer as backbones
2022
Starlink Tracking
A small D3.js-powered Satellite Tracking visualization
Travel Planner
A GPT-powered web application to help users automate travel plan suggestion, generation and archiving
Twitch+
A Search & Recommendation Engine for Twitch Streaming Video Resources
About
About Me I\'m Zhenlin Wang Criss . I graduated as an MS student from Machine Learning Department @ Carnegie Mellon University https://www.ml.cmu.edu/ . I have a strong passion for ...
Code Analyzer
C++ based code static program analyzer
2021
More on Model Deployment
Placeholder draft note preserved from the previous repository.
Variational Inference
A useful inference method for distributional approximation
Stats in ML: Dirichlet Distribution
A 'popular' distribution not widely known
An overview of Hidden markov model and its algorithms
Learning stochastic process with more details
SmartMall Discounted Electronic Shopping
A robust online shopping app with various middlewares serving the microservices architecture
Ensemble Models: Boosting Techniques
You know XGBoost, but do you KNOW XGBoost?
Variational Autoencoder (VAE)
Combine variational inference with representation learning
Ensemble Models: Bagging Techniques
Gather all we have!
Reinforcement Learning - Theoretical Foundations: Part IV
RL Continued - Value Function Approximation
Reinforcement Learning - Theoretical Foundations: Part V
RL Continued - Policy Gradient
Ensemble Models: Overview
Using the power of public
Reinforcement Learning - Theoretical Foundations: Part III
RL Continued - Model-free algorithms
Reinforcement Learning - Theoretical Foundations: Part II
RL Continued - Dynamic Programming
Reinforcement Learning - Theoretical Foundations: Part I
Finally the most intriguing part (to me)
2020
Gradient Descent Algorithm and Its Variants!
The most important technique in neural networks (as of now)
SQL: Going into Applications with MySQL and MongoDB
Going back to the technical details of what and how for popular SQL and NoSQL dbms
The Data Mining Triology: III. Analysis
Let the plot fly ~
SQL: Index and Optimization
A short guide on optimizing query performances
SQL: Pick up the Basic within a day
The best way to get the memory back is by looking at the code themselves
CLI-nic
Java-based medical resource management application
Database: Intro
A brief introduction to database system
A Regex Tutorial
Learn to process string operations in an efficient way
A fundamental course for Data Engineering
All you need for understanding industrial-level data
Apache Spark: Only the simple answer
Some conceptual understanding of spark and big data. Honestly, this just scratches the surface
Recommender Systems: III. Deep-learning Methods
Applications of Deep learning in recommender systems
Recommender Systems: II. Factorization Machine
Matrix factorization will save us from sparsity
Recommender Systems: I. Content-Based Filtering And Collaborative Filtering
Welcome to the world the recommenders
Dimension Reduction: Life savers
We must dispel the curse of dimensionality!
Unsupervised Learning: Measures about Clustering
We have clusters, and then?
Clustering: Apriori
Association Rule realized via inference
Clustering: Affinity Propagation
Affinity: voting with democracy
Clustering: DBSCAN
Graphical methods continued...
Clustering: Hierachial, BIRCH and Spectral
The nitty-gritty of 'brute-force'
Clustering: K Means and Gaussian Mixture Models
The basic models for clustering
An overview of Big Data Analytics
Know what data analysis is and for
2019
A brief Intro to A/B Testing
A Recap of Fundamental Concept: A/B Testing
The Data Mining Triology: II. Cleaning
The first step when you get some data: clean it up!
The Data Mining Triology: I. Preparation
Know how to get data from various sources and load them successfully
Topic Modeling with Latent Dirichlet Allocation
LDA using a great yet less popular distrbution
Hyperparameter Tuning
Unicorn is when your horn outshines others
Feature Selection & Model Selections
A rudimentary method forgotten by many practitioners nowadays
Some Supervised Learning Models
So, give me a taste of supervised learning
Regression Models: GAM, GLM and GLMM
A brief introduction to generalized regression
Model Validations and Performance Evaluators
How to determine if a model is truly good
Regression Models: Logistic Regression
Logit Model: the simple becomes the powerful
Regression Models: Linear Regression and Regularization
Shallow and Deep Linear Regression
MyPal
A Relationship Management System