Deploying Language Models With Gradio On Hugging Face

Machine learning models (including language models) can be easily deployed using generous free tier on Hugging Face and a python-based open source UI tool Gradio by following these steps. See live deployed app and source code here For local...

Machine Learning Notes

Contents Algorithms Bayes Explainability MLOps Model Evaluation Preprocessing Reinforcement Learning SQL Statistics Algorithms K-means: aims to choose centroids that minimize the inertia, or within-cluster sum-of-squares criterion. Use the...

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...

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...

Berkeley Earth Global Temperature Data

Berkeley Earth publishes an unique dataset with global temperature measurements. Below is a guide to the download the data and start analyzing it using Python. All code can be found in this gist. Download .txt file from Berkeley Earth data...

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...

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....

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...