MACHINE LEARNING

→ View original post on X — @mikequindazzi

Most Impactful Emerging Technologies for Business Predicted

By

@mikequindazzi

–

02 January 2023 17h44

Do you agree with #chatgpt3? >>> What do you predict will be the most impactful #EmergingTech on business? >>> #AI #Analytics #Automation #ImageRecognition #NLP >>> #CES2023

→ View original post on X — @sallyeaves

NASA STEM STEAM Education: 8 Ways Students Explore

By

@sallyeaves

–

02 January 2023 17h24

Break Down Boundaries! 8 Ways #Students Can Dive Into #STEM & #STEAM with #NASA in 2023 @NASA https://
bit.ly/NasaSTEAM #education @psb_dc @helene_wpli #Webb #dataScientist @TeachersPLN #Space #AI #ML @MatthewSekol @DigitalColmer @Paula_Piccard @michaeldacosta @IamNankpak

→ View original post on X — @abacusai

Abacus AI Simplifies ML Deployment with End-to-End Solutions

By

@abacusai

–

02 January 2023 17h00

The average machine learning engineer spends 98% of their time stitching services together. At @abacusai
, we take data from you, train a model, deploy it and give you an endpoint you can use immediately. Less complexity → More time to focus on what truly matters.

→ View original post on X — @deeplearn007

Top 2023 Tech Trends Predicted By AI Model

By

@deeplearn007

–

02 January 2023 16h38

Here Are The Top 2023 Trends As Predicted By An #AI Model : A Perfect Storm of Tech https://
medium.datadriveninvestor.com/here-are-the-t
op-2023-trends-as-predicted-by-artificial-intelligence-828a093a0ca6
… @pierrepinna @Xbond49 @PawlowskiMario @psb_dc @gvalan @TheRudinGroup @HaroldSinnott @mikeflache @Shi4Tech @Nicochan33 #MachineLearning #DeepLearning #Fintech #Datascience

2022 Conference Review Activity Across Seven ML Programs

By

–

02 January 2023 16h33

2022's year in reviews: I did 28 conference reviews, plus 42 meta-reviews, on 7 program committees (COLT, UAI, NeurIPS, SaTML, ICLR, USENIX Security, ALT). I also chaired two #ICML2022 workshops (TPDP and UpML). Numbers are down from last year, so why do I feel more tired…

Differential Privacy and Secure Aggregation in Federated Learning

By

–

02 January 2023 14h34

It's a bit complicated. Methods like differential privacy and secure aggregation on top of FL generally help, but there are some caveats. See "Is it possible to Prevent Our Passive and Active Attacks?" of http://
cleverhans.io/2022/04/17/fl-
privacy.html
….

→ View original post on X — @saboo_shubham_

Roadmap for Aspiring Machine Learning Engineers

By

@saboo_shubham_

–

02 January 2023 14h33

I understand your point. But this could act as a roadmap for someone just starting in the field who aspires to be an ML engineer.

Federated Learning: Heterogeneity and Privacy Perspectives

By

–

02 January 2023 14h19

I like FL as a lens through which to study heterogeneity in clients, which may have different distributions, resources, or capabilities. But not for privacy. Here is another perspective on privacy of FL, which is a bit more conspiratorial than my own https://
x.com/le_science4all
/status/1602432680657928193
…

Federated Learning Privacy Misconceptions Debunked

By

–

02 January 2023 14h14

~30% of true/false voters made the biggest misconception in privacy-preserving ML. Fact: federated learning is not private. @jasondeanlee and @tomgoldsteincs posted some nice papers showing this. Also, here's a blog explainer I like by @fraboeni et al.: http://
cleverhans.io/2022/04/17/fl-
privacy.html
…