ramikrispin

ramikrispin, 1 month ago to python

Thanks to @medium Staff for selecting my recent article - Introduction to Multi-Stage Image Build for Python 🐍, for a boost ❤️!

This tutorial provides a step-by-step guide for converting a regular Python Dockerfile into a multi-stage build 🚀.

🔗: https://medium.com/towards-data-science/introduction-to-multi-stage-image-build-for-python-41b94ebe8bb3

#python #docker #mlops #medium #datascience

ramikrispin, 1 month ago to python

(1/4) 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐌𝐮𝐥𝐭𝐢-𝐒𝐭𝐚𝐠𝐞 𝐈𝐦𝐚𝐠𝐞 𝐁𝐮𝐢𝐥𝐝 🐳 𝐟𝐨𝐫 𝐏𝐲𝐭𝐡𝐨𝐧 🐍

The size of the Docker image could quickly increase during the build time. I became more mindful of the image size when I started to deploy on Github Actions. The bigger the image size, the longer the run time and the higher the runtime cost.

This is when you should consider using a multi-stage build 🚀.

🧵👇🏼

#docker #mlops #python #DataScience #medium

ramikrispin, 1 month ago to ComputerScience

(1/2) Data Compression: Theory and Applications - Stanford Course 👇🏼

Stanford University released a new course on data compression methods taught by Prof.Tsachy Weissman, Shubham Chandak, and Pulkit Tandon. As the demand for data increases at an exponential rate, data compression plays a pivotal role in providing efficient storage solutions. The course focuses on the foundations and theory of data compression.

#data #computerscience

ramikrispin, 1 month ago to datascience

Forecasting Time Series with Gradient Boosting ❤️

The skforecast Python 🐍 library provides ML applications for time series forecasting using different regression models from the scikit-learn library. Here is a tutorial by Joaquín Amat Rodrigo and Javier Escobar Ortiz for time series forecasting with the skforecast using XGBoost, LightGBM, Scikit-learn, and CatBoost models 🚀.

📖🔗: https://cienciadedatos.net/documentos/py39-forecasting-time-series-with-skforecast-xgboost-lightgbm-catboost

#timeseries #forecasting #DataScience #MachineLearning #python

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ramikrispin, 1 month ago to llm

I am excited to present at the OSDC East conference next week about using LLM to create language to SQL code generator.

https://odsc.com/speakers/data-automation-with-llm/

#llm #datascience #MLops

ramikrispin, 1 month ago to llm

Llama 3 is already available on Ollama 🚀👇🏼

https://ollama.com/library/llama3

#llm #llama3 #ollama #python #DataScience

ramikrispin, 1 month ago to llm

(1/3) Llama 3 is out! 🚀

Meta released today Llama 3, the next generation of the Llama model. LLama 3 is a state-of-the-art open-source large language model. Here are some of the key features of the model: 🧵👇🏼

#llama #llama3 #llm #python #DataScience #MachineLearning #deeplearning

video/mp4

ramikrispin, 1 month ago to llm

RAG from Scratch with LangChain 🦜👇🏼

FreeCodeCamp released today a new course on building RAG from scratch with LangChain. The course, which is by Lance Martin from LangChain, focuses on the foundations of Retrieval Augmented Generation (RAG).

Course 📽️: https://www.youtube.com/watch?v=sVcwVQRHIc8
Code 🔗: https://github.com/langchain-ai/rag-from-scratch

#llm #rag #python #langchain #mlops

ramikrispin, 1 month ago to datascience

New release to Ollama 🎉

A major release to Ollama - version 0.1.32 is out. The new version includes:
✅ Improvement of the GPU utilization and memory management to increase performance and reduce error rate
✅ Increase performance on Mac by scheduling large models between GPU and CPU
✅ Introduce native AI support in Supabase edge functions

More details on the release notes 👇🏼
https://github.com/ollama/ollama/releases

Image credit: release notes

#DataScience #MachineLearning #llm #ollama #llama #python

ramikrispin, 1 month ago to datascience

Gemini API Cookbook 🚀

Google released a new repo with a collection of guides and examples for the Gemini API. This includes a set of guides for prompt engineering and examples of the API features 👇🏼

🔗 https://github.com/google-gemini/cookbook

#DataScience #MachineLearning #llm #deeplearning #Python

ramikrispin, 1 month ago to datascience

(1/3) Learn R Through Examples 🚀👇🏼

The Learn R Through Examples by Xijin Ge, Jianli Qi, and Rong Fan provides an introduction to data analysis with R. The book covers the core topics of data analysis using different datasets, from simple and clean datasets to messy and big datasets. 🧵👇🏼

#RStats #DataScience #datavisualization #data

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ramikrispin, 1 month ago to datascience

Happy Sunday!

Backpropagation Calculus 🚀🚀🚀

This short video by Grant Sanderson provides a great explanation of the math beyond the backpropagation algorithm using calculus 👇🏼

https://www.youtube.com/watch?v=tIeHLnjs5U8

#DataScience #math #deeplearning #MachineLearning

ramikrispin, 1 month ago to datascience

Hands-on Data Science: Complete your First Project 🚀

This beginner crash course by Misra Turp provides an introduction to the foundations of data science by solving real-life examples. This includes the different steps of a data science project, from setting the environment to loading and analyzing the data using Python, git, Jupyter notebooks and other tools 👇🏼

📽️: https://www.youtube.com/playlist?list=PLM8lYG2MzHmTgsYKLJtdKwf6tHVbui9eE

#DataScience #data #python

ramikrispin, 1 month ago to python

(1/2) A new release to PyMC 🚀🚀🚀

This week, PyMC version v5.13.0 was released. PyMC is one of the main #Python 🐍 libraries for 𝐁𝐚𝐲𝐞𝐬𝐢𝐚𝐧 statistics ❤️. It provides a framework for probabilistic programming, enabling users to build #Bayesian models with a simple Python API and fit them using 𝐌𝐚𝐫𝐤𝐨𝐯 𝐂𝐡𝐚𝐢𝐧 𝐌𝐨𝐧𝐭𝐞 𝐂𝐚𝐫𝐥𝐨 (MCMC) methods 🚀.

The new release includes new features, bug fixes 🐞, and documentation improvements 📖. More details on the release notes 📝 👇
#DataScience #machinelearning #statistics

stevensanderson, 1 month ago to github

Thoughts anyone, what do you think?

#R #RStats #RProgramming #chisquare #Distributions #parameter #estimation #GitHub #issue #Coding #Progrramming #HardProblem

Link: https://github.com/spsanderson/TidyDensity/issues/414

@r_constanzo
@ramikrispin
@bentoh
@jromanowska
@barubary
@RConsortium