Andy Gray 已转推
Andy Gray
636 posts

Andy Gray
@codingWithAndy
Lecturer of Computing at @BathSpaUni specialising in Artificial Intelligence & Machine Learning | ex-School Teacher of Computer Science |
Cornwall, Somerset and Wales 加入时间 Haziran 2017
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Andy Gray 已转推
Andy Gray 已转推
Andy Gray 已转推
Andy Gray 已转推
Andy Gray 已转推
Andy Gray 已转推
Andy Gray 已转推

We have a new tool to enable secondary students learning Python to use a more reflective process when debugging programs that don't run or don't work as intended. It's called PRIMMDebug and you can find out how to get involved in the testing here: computingeducationresearch.org/blog-introduci…
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Andy Gray 已转推

Are you one of over 1m people who overpaid their student loan last year? If so you can get your money, often £100s, back. My quick video briefing (including if it’s right for you to claim)…
Courtesy of @ITVMLshow (Tues 8pm)
Feel free to share with anyone it impacts
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Andy Gray 已转推

A free, online, hard-core Machine Learning book!
If you are interested in understanding how Machine Learning algorithms work, this is for you.
Great resource if you are one of those who cares about how the magic happens.
dafriedman97.github.io/mlbook/content…

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Andy Gray 已转推

Great opportunity for educators in Cornwall to become part of the team at Cornwall Research School.
Find out more information at researchschool.org.uk/cornwall/work-…

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Andy Gray 已转推
Andy Gray 已转推

📢 Calling all SW Pupil Premium Leads, Trust and Senior leaders. Book Addressing Disadvantage in Schools conference on Friday 27th Sept and hear from a range of speakers to discuss how your settings can address disadvantage for pupils.
Register at buff.ly/4gneyoW

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Andy Gray 已转推

Morning Brighton! Here for attending the @RSSAnnualConf, where @codingWithAndy is going to talk about our work on Bayesian comparative judgement, developed at the EPIC CDT (people-first.best) @CompFoundry. The supervisory team includs: @ProfTomCrick & @Slindsbob.

Brighton, England 🇬🇧 English
Andy Gray 已转推

To start with Machine Learning:
1. Learn Python
2. Start practicing using Jupyter
There are two main deep learning frameworks that everyone uses:
• TensorFlow
• PyTorch
Don't overthink this. Pick one of them and start practicing with it. I promise you'll end up learning both at some point.
You'll find many tutorials online but I usually struggle putting a good plan together, so I prefer courses that hold my hand from start to end.
Here are two of those programs:
• Introduction to Machine Learning with TensorFlow.
bit.ly/4fFu0wk
• Introduction to Machine Learning with PyTorch.
bit.ly/46JHQd0
These are the same program but one uses TensorFlow and the other uses PyTorch. Choose the one you prefer.
After you are done with this, you'll have accomplish something very important:
1. You'd have a large background on classical machine learning
2. You'd have a bunch of solved problems under your belt
Now, it's time to go much deeper. Here are some of the most advanced classes you can take:
• Udacity's Deep Learning Topics with Computer Vision and NLP
• MIT 6.S191 Introduction to Deep Learning
• DS-GA 1008 Deep Learning
• Udacity's Computing With Natural Language
• UC Berkeley Full Stack Deep Learning
• UC Berkeley CS 182 Deep Learning
• Cornell Tech CS 5787 Applied Machine Learning
I also love books! Look at the attached image. Those are some of my favorite machine learning books that I think you should consider.
Finally, keep these three ideas in mind:
1. Start by working on solved problems so you can find help whenever you get stuck.
2. Use AI to summarize complex concepts and generate questions you can use to practice.
3. Find a community and share your work. Ask questions and help others.
During this time, you'll deal with a lot. Sometimes, you will feel it's impossible to keep up with everything happening, and you'll be right.
Here are the good news:
Most people understand a tiny fraction of the world of Machine Learning. You don't need more to build a fantastic career in the space.
Focus on finding your path, and Write. More. Code.
That's how you win.

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Andy Gray 已转推

It's been a while, but I updated the GitHub repo with Interactive Tools for machine learning, deep learning, data exploration and math. 👇
Transformer Explainer
exBERT
BertViz
CNN Explainer
Play with GANs in the Browser
ConvNet Playground
Distill: Exploring Neural Networks with Activation Atlases
A visual introduction to Machine Learning
Interactive Deep Learning Playground
Initializing neural networks
Embedding Projector
OpenAI Microscope
Atlas Data Exploration
The Language Interpretability Tool
What if
Measuring diversity
Sage Interactions
Probability Distributions
Bayesian Inference
Seeing Theory: Probability and Stats
Interactive Gaussian Process Visualization
github.com/Machine-Learni…

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Andy Gray 已转推

Self-RAG (@AkariAsai et al.) is a popular advanced RAG technique that came out last year that adds a dynamic element to RAG - dynamically determine which chunks are relevant to the query instead of stuffing all the context in.
We’ve created a variety of resources here, but in case you missed it, @kingzzm has an excellent flow diagram outlining all the key steps, including the three parts of evaluation: is relevant to query, if chunk support the answer, and if the generated answer is helpful for the query.
It also contains an overview of our LlamaPack!
Full blog here: ai.gopubby.com/advanced-rag-r…
Self-RAG LlamaPack: llamahub.ai/l/llama-packs/…

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Andy Gray 已转推

An amazing working group of teachers and others have put together a booklet on generative AI for computing teachers. It's full of tips and examples, and a glossary of terms. We really hope you find it useful. Please share if you do. computingeducationresearch.org/blog-using-gen…

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Andy Gray 已转推

👏 Congratulations to @ProfTomCrick, @AlmaRahat and @DrSeanWalton who have been announced among a new cohort of 51 Turing Fellows to have joined @turinginst to tackle societal challenges.
Learn more:
➡️ swan.ac/Turing

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Andy Gray 已转推














