Al Christopher

Big Data and Data Science Community Leader

[Akshay 🚀 @akshay_pachaar]

The easiest way to find out which models you can run on your computer:

1) Install
npm install -g llm-checker

2) Detect your hardware
llm-checker hw-detect

3) Get recommendations by category
llm-checker recommend --category coding

Credits to @svpino for bringing this to my attention. I found it super useful and thought of sharing it with you all.

Here are some of the recommendations I got:

[Al Christopher @allen_tools]

@pumbadev lumbar - skweek - what wowclassic server should I use?

[Al Christopher @allen_tools]

@JimCarrey i'd like to tech and AI stuff with you and your artwork, in with being your protege, I feel like we'd get with brilliant works.

[Al Christopher @allen_tools]

I’m LIVE 🤳 🎥 on #Badoo! Watch now! 🙌 https://t.co/c5uCufoaL9

[Al Christopher @allen_tools]

I’m LIVE 🤳 🎥 on #Badoo! Watch now! 🙌 https://t.co/qOEf2HEzJh

[Hilary Mason @hmason]

AI is not inscrutable magic -- it's math and data and computer programming, made by regular humans.

People who make AI are not unicorns. They are just people who like math and data and computer programming. https://t.co/OGcv35yoZ5

[Georgina Cosma @gcosma1]

Great resource! A Survival Guide to Data Science with R – using templates (w/ R code) #datascience #MachineLearning #DataAnalytics #Statistics #rstats https://t.co/b3A9wUpwur

[Al Christopher @allen_tools]

Are Data Scientists Earning Their Salaries? | WIRED https://t.co/wcO4HnP5rw

[Al Christopher @allen_tools]

Easy and simple goodness! I love how ml is coming along! https://t.co/X3KKdppzDL

[Mike Tamir, PhD @MikeTamir]

GluonCV — Deep Learning Toolkit for Computer Vision https://t.co/yOquGxWqZj #AI #DeepLearning #MachineLearning #DataScience

[/MachineLearning @slashML]

Simple Tensorflow implementation of "Self-Attention GAN" (Han Zhang, Ian Goodfellow) https://t.co/V9TtMbBTpz

[FakerFact @Faker_Fact]

More resources:
Announcing Open Images V4 and the ECCV 2018 Open Images Challenge https://t.co/JgYTir8Cjc #AI #DeepLearning #MachineLearning #DataScience

[Unit for Natural Language Processing @UNLP_Galway]

If you are still at #NAACL2018 come to talk with @OmniaHZayed abt our work on phrase-level metaphor identification at the #FigLang18 poster session this afternoon ;) #NLProc @insight_centre @DSIatNUIG

[Georgina Cosma @gcosma1]

Really useful! Multiple output classification with Keras (step by step guide w/ Py code) #DataScience
#MachineLearning #DeepLearning
https://t.co/Jle7Wkr8Ak

[NVIDIA AI @NVIDIAAI]

.@MayoClinic researchers use #deeplearning to classify ultrasound images for an affordable early detection solution in the fight against breast cancer. https://t.co/7jymEFqpK4

[Analytics Vidhya @AnalyticsVidhya]

Let's learn the complete process of Web Scraping in R and gain expertise to use any type of data available over the Internet, with this guide, here. https://t.co/ByqpEbKSV4 #MachineLearning #Rstats

[Mara Averick @dataandme]

😻 the handiest:
"Probability Cheat Sheets" by @wzchen & @stat110
https://t.co/q7aIsGIk1f #probability #statistics #SoDS18

[Al Christopher @allen_tools]

https://t.co/hxiJpJnsv4 For anyone wanting to learn enough linear algebra to have a good understanding of it in a few days (assuming you have a mathematics background in calculus and statistics already) this series based on Ian Goodfellow et al. Deep learning book is exceptional!

[Mike Tamir, PhD @MikeTamir]

What is AI, really? – AI-First Design – Medium https://t.co/2ThQvWPnIX #AI #DeepLearning #MachineLearning #DataScience

[Arthur Mensch @arthurmensch]

Our work w/ @mblondel_ml 'Differentiable Dynamic Programming for Structured Prediction and Attention' was accepted at @icmlconf ! https://t.co/1QHoxo2rpT Sparsity and backprop in CRF-like inference layers using max-smoothing, application in text + time series (NER, NMT, DTW)