Rami Krispin

My weekly newsletter is out! 👇🏼

open.substack.com/pub/ramikris...

#datascience #rstats #python

Time Series Forecasting in Python, the DuckLack R Library, New Tutorials| Issue 76 A weekly curated update on data science and engineering topics and resources.

My weekly newsletter is out!

This week's agenda:
🔹 Open Source of the Week - The DuckLack R project by Travis Gerke, ScD
🔹 New learning resources
🔹Book of the week - Time Series Forecasting in Python by Marco Peixeiro

ramikrispin.substack.com/p/time-serie...

#rstats #python #ai #datascience

YouTube video by Alejandro AO Fine-Tune an Open Source LLM with Claude Code/Codex (Hugging Face Model Trainer Skill)

Fine-Tune an Open Source LLM with Claude Code/Codex 👇🏼

The following tutorial by Alejandro AO provides an introduction for fine-tune a small open source model with Codex using the Hugging Face model trainer skill and HF Jobs.

www.youtube.com/watch?v=HGPT...

#ai #llm

I am going to run a workshop tomorrow about running LLMs locally with Docker Model Runner.

If you want to join, please RSVP:
www.eventbrite.com/e/hands-on-r...

#ai #llm #docker

The KAOS Project, Relational Database Book & New Tutorials Explore the KAOS open-source project, a new relational database book, and top tutorials on Python, AI, systems, and data engineering in this curated weekly roundup.

My weekly newsletter is out!

This week’s agenda:
🔹 Open Source of the Week - The KAOS project
🔹 New learning resources
🔹 Book of the week - Grokking Relational Database Design by Qiang Hao and Michail Tsikerdekis

ramikrispin.substack.com/p/the-kaos-p...

#ai #datascience #dataengineering

The Shapash Project, New Python Book, OpenClaw Tutorials | Issue 74 Discover the Shapash open-source explainability project, a new Python book, OpenClaw tutorials, and top AI/ML learning resources in this curated weekly roundup.

My weekly newsletter is out 👇🏼

This week’s agenda:
- Open source - The Shapash project
- New tutorials
- Book of the week - Software Design for Python Programmers by Ronald Mak

ramikrispin.substack.com/p/the-shapas...

#ai #machinelearning #python

I am happy that a wall is separating me from this cut bobcat 😅

Only in California—sitting in a meeting room while a bobcat elegantly strolls by outside 🐾

I had the same question, but I did not have the time yet to explore this library.

Capture this great view of San Francisco this morning 👇🏼

caretForecast Conformal Time Series Forecasting Using Machine Learning

The hexagon here is priceless 😎

taf-society.github.io/caretForecast/

#rstats #timeseries

The QueryChat Project, Mathematics of Machine Learning, New Tutorials Explore the QueryChat open-source project, math foundations of machine learning, and fresh tutorials on MLOps, data engineering, and AI tools in this curated roundup.

My weekly newsletter is out 👇🏼

Open source: the QueryChat
New tutorials
Book: Mathematics of Machine Learning

ramikrispin.substack.com/p/the-queryc...

#python #rstats #ai

Introduction to Multi-Stage Image Build for Python This post introduces the Multi-Stage build approach for setting up a lightweight dockerized Python development environment.

💡 Why it matters: smaller images → faster CI/CD → less storage & network cost → reduced attack surface → happier developers.

If you want to learn more, please check my tutorial about multi-stage build:

medium.com/data-science...

5️⃣ Install Only What You Need

Separate dev dependencies from production deps.

Use flags like --no-dev or careful requirements files so you install only what your app actually needs at runtime.

4️⃣ Use .dockerignore to Cut Build Context

Exclude unnecessary files (.git, logs, IDE folders, virtual environments) so Docker doesn’t send them into the build context — this keeps images lean and speeds up builds.

3️⃣ Minimize Layers

Every RUN / COPY / ADD adds a layer.

➡️ Combine related commands with && to reduce layers and eliminate intermediate files (although you won't gain much size reduction).

Fewer layers = smaller image.

2️⃣ Use Multi-Stage Builds (Big Win!)

Multi-stage builds let you install tools and build dependencies in one stage, then only copy what’s needed into a clean final image. This can reduce the size by 60-90% compared to single-stage builds.

1️⃣ Choose a Lean Base Image

Start smaller:

✔️ python:3.x-slim instead of the full Python image

✔️ python:3.x-alpine if compatible with your dependencies (and you are a brave developer 😆)

Smaller base = smaller final image and faster pulls.

Are you working with Python inside Docker containers? Here's how you can make your images slimmer 🐳🧵👇🏼

#python #docker #mlops

Pandas 3 Release, Machine Learning Systems & New Tutorials | Issue 72 Learn what’s new with Pandas 3, get ML systems insights, and explore top tutorials on JAX, FastAPI, and more in this curated data science roundup.

My weekly newsletter is out!

Open source: Pandas 3 release
New tutorials
New book: Introduction to Machine Learning Systems by Prof. Vijay Janapa Reddi

ramikrispin.substack.com/p/pandas-3-i...

#ai #python #machinelearning

Pandas 3 is out! 👇🏼

pandas.pydata.org/community/bl...

Fun fact - pandas stands for PANel DAta and Spython.

#python #data

YouTube video by Corey Schafer Python FastAPI Tutorial (Part 1): Getting Started - Web App + REST API

Getting started with FastAPI 👇🏼

www.youtube.com/watch?v=7AMj...

YouTube video by Google for Developers Why JAX and Flax NNX?

Introduction to JAX and Flax NNX - the framework behind Google Gemini 👇🏼

www.youtube.com/watch?v=fcX0...

Statistical Analysis with Python, SQLGlot & MIT Deep Learning | Issue 71 A weekly curated update on data science and engineering topics and resources.

My weekly newsletter is out 👇🏼

Project: SQLGlot
New tutorials
Book: Statistical Analysis with Python

ramikrispin.substack.com/p/statistica...

#datascience #python #ai

YouTube video by Learn Linux TV This Bash Trick Makes cd Much More Useful!

This is super cool 👇🏼

www.youtube.com/watch?v=DsmK...

Automate Change Point Detection in Time Series with Piecewise Regression A practical grid search approach for detecting trend changes in time series data

This tutorial is also available on Medium for subscribers:
medium.com/p/2abc6c9309c6

And we're live, Lecture A1 is online. Introduction to Bayesian workflow, generative models, estimands, estimators, estimates, error checking, beginnings of probability theory and Bayesian updating. www.youtube.com/watch?v=ztbY...

Here is an illustration of a stateless AI app 👇🏼

Setting Up a Memory for an AI Application - The Hard Way LLM Memory Explained: Building Short-Term Conversational Memory in Python

By default, LLMs don’t come with memory, and each conversion is independent of the previous one. How do you add memory to an #AI application? Apparently, it is simpler than it sounds, and it takes less than 5 lines of code to add one. Here is how:

theaiops.substack.com/p/setting-up...

#python #llm

I couldn't stop laughing 😆

Credit: Eduardo Ordax