Machine Learning Notes

Collection of AI, ML, and data resources I've found useful. Contents Algorithms Bayes Explainability MLOps Model Evaluation Preprocessing Reinforcement Learning SQL Statistics Algorithms AdaBoost: Fits a sequence of weak learners on repeatadly...

Machine Learning Docker Template

Contents Summary Code Summary The purpose of this post is to propose a template for machine learning projects that strives to follow these principles: All data scientists can quickly setup an identical development environment based on Docker that...

Keras LSTM Forecasting Using Synthetic Data

Contents Summary Notebook Summary Keras LSTM can be a powerful tool for forecasting. Below is a simple template notebook showing how to setup a data science forecasting experiment. Dataset A synthetic dataset was generated using a scikit-learn...

Scikit-learn Pipeline with Feature Engineering

Contents Summary Notebook Summary In general, a machine learning pipeline should have the following characteristics: To ensure data consistency, the pipeline should include every step (such as feature engineering) required to train and score training...

Global Temperature Forecast Using Prophet and CO2

In this article I will leverage the global temperate dataset I discussed previously to make a temperature forecast using Facebook Prophet for the next 50 years. Note: the temperature dataset serves ONLY as a vehicle to learn how to do forecasting...

Dynamic HTML with Python, AWS Lambda, and Containers

This article is an extension of my previous article describing a similar deployment process using native AWS Lambda tools. However, Amazon since started supporting container images and updated it’s pricing policy to 1ms granularity. Both are major...

Google Colab and Auto-sklearn with Profiling

This article is a follow up to my previous tutorial on how to setup Google Colab and auto-sklean. Here, I will go into more detail that shows auto-sklearn performance on an artificially created dataset. The full notebook gist can be found here. First,...

Google Colab and AutoML: Auto-sklearn Setup

Auto ML is fast becoming a popular solution to build minimal viable models for new projects. A popular library for Python is Auto-sklearn that leverages the most popular Python ML library scikit-learn. Auto-sklearn runs a smart search over...

Serving Dynamic Web Pages using Python and AWS Lambda

While AWS Lambda functions are typically used to build API endpoints, at their core Lambda functions can return almost anything. This includes returning html markup with dynamic content. I will not go into details describing how to deploy AWS Lambda...

Custom VPN using PiVPN and public cloud

Motivation: Many public Wi-Fi networks block certain internet ports and protocols. For example, a public library might only allow ports 80 and 443 and the TCP protocol. Leaving aside the logic of such decisions by network owners, they prevent users...