Richard Ball

Principal Data Scientist

[Richard Ball @ball_rs]

@lukebelmar Run Hermes 4 from @NousResearch on @lmstudio. Totally unhinged ;)

[Richard Ball @ball_rs]

Found a scanned copy: https://t.co/NoFmRSsaW1
https://t.co/2yjAGJtm4o

[Dylan Abruscato @DylanAbruscato]

Lots of folks have been asking how I came across the little Sequoia book.

It’s a ~70-page book about Don Valentine and the history of Sequoia, written by Michael Moritz.

Here’s the wild story—and how you can probably find one too:

[Richard Ball @ball_rs]

@DylanAbruscato Here's a scanned version: https://t.co/NoFmRSsaW1

[Richard Ball @ball_rs]

@ricburton My salt gun to chase away those pesky summer flies.

[Richard Ball @ball_rs]

@thesamparr Also good is ErikTheEletric https://t.co/Nz55OeCEaY

[Evidently AI @EvidentlyAI]

How to enhance ML monitoring with synthetic data?

@ball_rs used it to generate test data and trigger data drift on demand with Evidently as a monitoring tool.

This use case is helpful for testing alarms in advance and simulating data drift scenarios👇
https://t.co/ovnbkB9ZPT

[Anonos @anonos]

One of the biggest obstacles to using #machinelearning for #frauddetection is the lack of available training data. Our latest blog explores different approaches to training #ML models for credit card fraud detection, including SMOTE & #syntheticdata: https://t.co/gflGIeHACC

[Richard Ball @ball_rs]

@bznotes Small passport holders like this work really well: https://t.co/3HQ2v0zx4e

[PyG @PyG_Team]

Looking to use graph learning in financial networks?
We got some great tutorials for you!

Fraud Detection:
https://t.co/WvX3AT64Ae
https://t.co/s4QkM3sdGe

https://t.co/VlhUOMP7H8

Capture illegal transactions:
https://t.co/QIieSkDS9D
https://t.co/kINdl4nl5T

[Mike Tamir, PhD @MikeTamir]

Supervised Clustering: How to Use SHAP Values for Better Cluster Analysis https://t.co/7WKYgRUJou
#AI #MachineLearning #DeepLearning #DataScience

[Rishabh (in SF) @rishabh16_]

🚨 My Graph Deep Learning extended tutorial has a new home!!!

It's finally up on my personal website:
https://t.co/EdfHc18L75

Do RT, share, and tag your GDL buddies if you find it useful 🙌🏻🙌🏻

[Hypertext @htxtafrica]

Luno looks at who is buying crypto in South Africa https://t.co/LCZVIVZOjl

[Ventureburn @Ventureburn]

Luno data reveals the habits of the South African crypto buyer https://t.co/S0P8cez7cx

[Business Day @BDliveSA]

SA’s crypto investors are overwhelmingly male, Luno data shows https://t.co/4GRTwASwb8

[iO Academy @IOAcademyUK]

Have you got a burning question about our new #DataScience course? Perhaps you're keen to know what a job in #MachineLearning could look like?

We're hosting a Q&A session just for you.

Join us on 16th March & ask @MPOram & @richardball_ anything ➡️ https://t.co/4ocBKqZbl1

[Forvis Mazars in South Africa @ForvisMazars_SA]

Join our digital assets, audit and data experts as they unpack the role that big data plays in the world of virtual asset providers, how they go about managing and securing it, and how we as Mazars audit this data. https://t.co/lkHfgOLlXq
#crypto #cryptocurrency #dataanalytics

[Business Day @BDliveSA]

WATCH: Local investors see opportunity in crypto market https://t.co/rahZvzi2GG

[Henri Zietsman @HenriZietsman]

@LunoGlobal 🇿🇦🔥🍭👇👇 Boosts Fraud Detection with #AWS-Powered Machine Learning! @AWSstartups @Sonzaazism https://t.co/eG2hFcTJjD

[Evidently AI @EvidentlyAI]

Are you using @MLflow to log the experiments? You can now use it with Evidently to monitor models too.

Here is how you can run checks for data drift with Evidently and display results in MLflow UI:

Tutorial: https://t.co/A9Ykqjs6Qu
Example notebook: https://t.co/blmDzxoEWI

[Richard Ball @ball_rs]

@StuartReid1929 You may find this interesting: https://t.co/9PuNxagniM