Andrew Ng's new Deep Learning Course ππΌ
www.youtube.com/watch?v=_NLH...
#ai #deeplearning
@ramikrispin.bsky.social
Senior Manager Data Science and Engineering at ο£Ώ | Docker Captain π³| Time-series analysis & forecasting My newsletters: Weekly updates: https://ramikrispin.substack.com AIOps: https://theaiops.substack.com Forecasting: https://theforecaster.substack.com
Andrew Ng's new Deep Learning Course ππΌ
www.youtube.com/watch?v=_NLH...
#ai #deeplearning
A great illustration of how the Support Vector Machine algorithm is working:
substack.com/home/post/p-...
#machinelearning
I came across the Foretell project todayβan R library for forecasting customer retention based on Fader and Hardie et al. probability mixture models. Looks really interesting for those working with cohort data π:
github.com/sriharitn/fo...
#RStats
This short tutorial by Shaw Talebi focuses on building an MCP server and using it to create a YouTube AI agent.
www.youtube.com/watch?v=w-Ml...
#ai
I really love the Net Ninja channel content. This crash course by Net Ninja focuses on implementing AI into the coding workflow using GitHub Copilot with VS Code.
www.youtube.com/playlist?lis...
#AI
I have accumulated 13 random Docker tutorials on Medium over the past two years for both #rstats and #python, and for #VScode. I created a list with links:
medium.com/@rami.krispi...
My weekly newsletter is out!
This weekβs agenda:
πΉ Open Source of the Week - The quarto-svelte project
πΉ New learning resources -
πΉ Book of the week - R for Economic Research (second edition) by J. Renato Leripio
ramikrispin.substack.com/p/issue-56-r...
#rstats #ai #machinelearning #quartopub
I had the pleasure of attending and presenting at the LinkedIn AI in Work Day this week in San Francisco. I created a short summary of the talks and insights about the impact of AI on the job market.
www.linkedin.com/pulse/ai-wor...
Thanks, Australia π¦πΊ, for acknowledging that reviewing and submitting PRs can be a stressful process π
Image credit: Cybernews
If you want to learn more about using GitHub templates: theaiops.substack.com/p/from-zero-...
29.09.2025 13:32 β π 1 π 0 π¬ 0 π 0β‘οΈ Updated the build to multi-arch, supporting both arm64 and amd64 CPU architectures. This is super useful for cases where you are using Apple Silicon locally and deploy to GitHub Actions (or other systems) that are running on amd64 architecture
29.09.2025 13:32 β π 0 π 0 π¬ 1 π 0I made the following updates that make this template more efficient:
β‘οΈ Separated the image into two builds - dependencies (e.g., tools, Debian libraries, etc.) and the Python environment. This reduces the build time when starting a new project from minutes to seconds
The goal of using a GitHub template is to reduce the cost of starting a new project. My Python template includes a clone of my local CLI tools (zsh, oh-my-zsh, etc.), core Debian dependencies, VScode settings, and UV settings to create a virtual environment.
github.com/RamiKrispin/...
I updated my Python π Dockerized π³ development environment template over the weekend ππΌ
#python #docker #vscode #github
My weekly newsletter is out!
This week's agenda:
πΉ Open Source of the Week - The TimeCopilot Project
πΉ New learning resources
πΉ Book of the week - Modern Deep Learning Foundations by Dr. Barak Or
ramikrispin.substack.com/p/the-timeco...
#timeseries #ai #machinelearning
This is the way!
youtu.be/_pa1KLXuW0Y?...
Having a Docker/Airflow setting issue:
-The time it would take me to figure out the issue (Google it, trial and error, and Google again, etc.), probably ~1 hr
-The time Claude Code identifies the issue and comes up with the right setting ~1m
Now, scale it on a yearly basis - that is a great ROI
#ai
This looks like a super interesting project π
github.com/AzulGarza/Ti...
#ai #timeseries #forecasting
And my R template:
github.com/RamiKrispin/...
#rstats
Here is an example for a Python template:
github.com/RamiKrispin/...
#python
If you don't have a Medium subscription, the tutorial is available in my newsletter, The AIOps Newsletter, along with other tutorials.
theaiops.substack.com
The following tutorial focuses onΒ efficiently setting up a new Dockerized development environment with minimal time usingΒ GitHub repository templatesΒ withΒ VScodeΒ and theΒ Dev ContainersΒ extension.
The tutorial is available on Medium:
medium.com/p/6193f6d4ecb4
#docker #github #mlops #vscode
My weekly newsletter is out!
This week's agenda:
πΉ Open Source of the Week - The JuLS project
πΉ New learning resources
πΉ Book of the week - Model to Meaning by Vincent Arel-Bundock
ramikrispin.substack.com/p/the-juls-p...
#Julialang #RStats #python #datascience
The fourth tutorial in the Docker Model Runner series focuses on working with LLMs locally with R using the ellmer library:
medium.com/data-science...
#ai #rstats #docker
The following short tutorial provides great tips for using Claude Code:
www.youtube.com/watch?v=rfDv...
My weekly newsletter is out!
This week's agenda:
πΉ Open Source of the Week - ggplot2 new release
πΉ New learning resources
πΉ Book of the week - Regression and Other Stories
ramikrispin.substack.com/p/the-ggplot...
#rstats #python #ai #datascience
I asked to create a diagram that explains the Airflow DAG and it created it with mermaid, so I asked if it can create it with Draw.IO and simply did. If it crashed or stuck, you should restart and try again
12.09.2025 17:43 β π 1 π 0 π¬ 0 π 0When you are brainstorming with Claude Code about building a data pipeline and ask it to create documentation and a diagram π€―
#ai #claude
Issue 12 of RDM Weekly is out! π«
It includes:
- Navigating Open Research for Early Career Researchers from CONUL Research Group
- Shaping Responsible AI @researchdataall.bsky.social
- Beginnerβs Guide to Web Scraping in Python @spsanderson.com
and more!
rdmweekly.substack.com/p/rdm-weekly...
Stanford released the new version of one of the most popular Stanford Deep Learning courses - Deep Learning for Computer Vision, taught by Prof. Fei-Fei Li, Prof. Ehsan Adeli, Prof. Justin Johnson, and TA Zane Durante.
π½οΈ: www.youtube.com/playlist?lis...
#ai #deeplearning #machinelearning