Archive

the year is almost over, and SO MUCH is happening. Check out the workshop and my giveaway! But before that, some machine learning!

The Latest Fashion

• Do you look at Pytorch tensors to figure out what’s wrong? Try lovely-tensors to get an intuitive overview instead!
• I have been reading more about git recently. This Idiot proof git workflow was quite interesting to follow!
• I found this intersectional AI toolkit quite fascinating! A good resource to keep around and make AI more equitable.

Got this from a friend? Subscribe here!

it’s a lovely day and the weekend is near. Let’s enjoy some machine learning together!

The Latest Fashion

• Stable Diffusion has made quite the stride in just a few months. This Twitter thread gives a nice overview.
• Alternatives to Github Copilot are rare, for now. Huggingface is inviting AI researchers to contribute to BigCode.
• Difftastic is a diff program that understands syntax!

Got this from a friend? Subscribe here!

I’m unfortunately still not doing well, so we’ll have a shorter issue today. So let’s enjoy some machine learning!

The Latest Fashion

• The next level in using Stable Diffusion is installing a WebGUI instead of using Huggingface spaces and this InvokeAI fork is pretty comprehensive and open source!
• Writing tests for machine learning can feel daunting. This article makes writing robust tests for data and ML more accessible!
• This AI4Code Kaggle challenge is very nice to read through (and there’s 7 days left).

Got this from a friend? Subscribe here!

your eyes do not deceive you; this is a new issue on an actual Friday! I’m sick at home, so let’s cheer up with some machine learning!

The Latest Fashion

• This website explains any part of any paper that you highlight and allows follow-up questions.
• The Follower connects open camera data with AI to find live footage of influencers in the wild. Yes, it’s as creepy as it feels.
• I’m low-key obsessed with Stable Diffusion; here is a collection of open prompts.

Got this from a friend? Subscribe here!

this week had more deadlines than days and I’m severely jetlagged. However, this is the 100th issue of this newsletter! How could I not share more awesome things?! Let’s dive into some machine learning!

The Latest Fashion

• I love a good “Awesome List” and this one is on Diffusion Models!
• Scikit-learn and huggingface join forces to serve classical ML models
• Registrations opened for a new MOOC for machine learning in weather & climate prediction

Got this from a friend? Subscribe here!

if you go back and analyse how many newsletters were late and which ones mention that I’m stressed, I think there’s some overlap. But regardless, there has been some amazing machine learning going one, so let’s check those out for a break!

Also welcome to all those 100s new subscribers! We’re over 850 now!

The Latest Fashion

• The State of AI report for 2022 just dropped.
• Selecting features in data science is important. LOFO-importance for feature selection automates this selection by leaving a feature out and retraining.
• Kaggle published their data from the 2022 ML and data science survey.

I’m back in the office playing catch-up. The last quarter of the year has started, and I feel behind on everything. I know I tend to do too much, but is it finally catching up to me? Anyways, let’s catch up on some awesome machine learning!

The Latest Fashion

• Can AI discover new scientific insight? Well, Deepmind just published a paper discovering new efficient ways to multiply matrixes that are larger than 2x2!
• I love the illustrated guide to transformers. Here’s the new illustrated guide to stable diffusion.
• You’ve just learned about stable diffusion? How about using it to generate whole videos. Incredible.

Got this from a friend? Subscribe here!

it’s been a while! My vacation made me forget the time, as it should, so I completely missed last week. Apologies! But I’m back at my desk now. Full of energy. Ready to take on the world of machine learning! So let’s dive in.

The Latest Fashion

• You know the advice to not “copy and paste commands” because it’s unsafe and you still always do? Shellfirm tries to secure your shell for risky command patterns like deleting everything with rm -rf *
• This article uses language as a means to explain machine learning generalization with neat illustrations!
• Gaussian Processes sometimes seem to be on the fringes of modern machine learning, but they’re incredibly useful.

Got this from a friend? Subscribe here!

I’m still on vacation in Mozambique. Went for my first dives and it’s a blast. But that won’t keep us from some awesome machine learning! Masks on, regulators in, let’s dive into it!

The Latest Fashion

• Quantus is an explainable AI library that looks very promising with different metrics across different factors of XAI
• The Scipy 2022 Machine Learning & Data Science talks are on Youtube!
• Ever wanted to learn CUDA? You could try these GPU puzzles to get started.

Got this from a friend? Subscribe here!

I just emerged on a beautiful beach in Mozambique after 3 days of travelling, apologies for the delay! The next few newsletter issues will be reduced to still share awesome things with you, while honoring that I am on vacation. But I genuinely enjoy writing these issues too much to skip them completely, so let’s dive into some machine learning!

The Latest Fashion

• How about a $250,000 USD cash grant for your AI-native product idea to kick things off? The AI grant is by some awesome people for awesome people so check it out!
• This Hacker News thread on the proper way to get into ML in 2022 was fun to browse
• How about giving your torch tensor dimensions names instead of guessing the index?

Got this from a friend? Subscribe here!

I’m on my way home from Euroscipy and it was a blast. But that won’t stop us from awesome machine learning, right? Let’s dive right in!

The Latest Fashion

• Wanted to use Imagen or Dall-E 2 but not an AI influencer? The Stable Diffusion release enables anyone to try state-of-the-art text-to-image diffusion models (even in Colab!).
• Reproduce recent papers in the paperswithcode reproducibility challenge.
• Dreamworks open-sourced their rendering engine for you to play around with.

Got this from a friend? Subscribe here!

it’s been 2 years of this newsletter! 🥳

In these anniversary issues, I like to go through the last year of writing this weekly newsletter and see what everyone liked. So, in case you missed these awesome links, this is what everyone else enjoyed!

The Latest Fashion

• The Explainer Dashboard for interactive exploration of machine learning models
• Messing up code is easy, and https://dangitgit.com to find the right command to untangle the mess
• Everyone loved the idea of easier matplotlib subplots with mosaics.

finally, I’m coping with the heat. I’m back to writing regularly and contributing at work and in my projects. Lovely! So let’s look at some machine learning!

The Latest Fashion

• This collection of over 200 machine learning flashcards is really neat.
• Never Trust A Number – was a fascinating piece of insight.
• Chip Huyen wrote an intro to streaming data for data scientists.

Got this from a friend? Subscribe here!

it’s been a rough week over here. But it feels like I’m just recovering in time to share some awesome machine learning with you! Let’s dive in!

The Latest Fashion

• This is a fantastic comparison of state-of-the-art computer vision models.
• Andrew Ng has a new machine learning course, updating the classic Coursera course everyone took.
• For production-grade graphs of neural networks, I love PlotNeuralNet.

Got this from a friend? Subscribe here!

it’s finally cooling down over here. The sun is nice and all, but above 20°C, my brain just stops working. But that shouldn’t stop us from finding some awesome machine learning and some Python this week! Let’s dive right in!

The Latest Fashion

• The creator of XKCD started playing around with DALL-E 2 exploring Pokemon cards throughout the ages.
• Matplotlib has a Mosaic API that seems really cool for subplots I didn’t know about!
• Truss promises to serve ML models without boilerplate. Enticing!

Got this from a friend? Subscribe here!

It’s been a good week over here. There are now 600+ people reading these weekly emails, which is incredible. Hope you have a great start into the weekend. Now for some machine learning!

The Latest Fashion

• Version 5 of the Practical Deep Learning for Coders course just dropped.
• I guess today is a Jeremy Howard issue since his guide to matrix calculus for deep learning is really great.
• This repo has PyTorch code, models, and pre-trained weights for all your favourite deep learning vision architectures.

Got this from a friend? Subscribe here!

it’s my birthday today! 🎂 So, before I’m off to celebrate, let’s look at some awesome machine learning!

The Latest Fashion

• Last week I shared the Dall-E 2 prompt book. Now you can sign up to the open Dall-E 2 beta.
• Most practitioners know tabular data is for xgboost. This new paper by Gael Varoquaux et al backs this up.
• Meta of all places launches a tool Wikipedia is using for fact-checking. It’s so weird, I lapped up the article about it.

Got this from a friend? Subscribe here!

I’m running late! I got carried away building a new website. But that shouldn’t keep us from this awesome machine learning on a Friday!

Also, we’re over 555 people now! Incredible! Big Hello to all these new nerds as well. Enjoy the links!

The Latest Fashion

• Normally, I’m tired of new large language models, but the BLOOM big science model was created collaboratively by over 1000 researchers in 59 languages. That’s pretty neat.

• Ever mess up in git and spiral down a rabbit hole of StackOverflow answers? Dangit, Git?! is a nice overview of the most common fixes you may need.

• Playing with DALL-E and imagen can be tricky. This DALL-E 2 prompt book teaches you how to get better outputs by thoughtful prompt design.

we’re now over 500 people on this niche newsletter! Incredible! Welcome to all the new machine learning enthusiasts. Hope you find something new! So let’s dive right into some machine learning!

The Latest Fashion

• Quickly deploy a dashboard with extensive explainability for your ML models.
• Data Structures and Algorithms is easily the most impactful class in computer science class I have taken, here is a fantastic study guide.
• There’s a new $1000 monthly Kaggle award when you replicate an ML research paper.

Got this forwarded by a friend? Subscribe here!

it's been a mixed bag of a week. The weather is great and I made fantastic progress, but the state of the world is still shocking. Anyways, let's look at some machine learning.

The Latest Fashion

• Pen and Paper Exercises in Machine Learning just dropped. It’s fairly basic with a focus on math instead of applied ML or models, but insightful in that regard and great for preparation for technical interviews.

• Google Brain have published a paper on their reinforcement learning efforts to aide designing chips for the latest generation of TPU chips.

• Still wonder what these transformers are all about? Here’s an opinionated guide to transformers, from basics to implementation and theory.

My Current Obsession

I went viral this week and put a massive amount of effort into creating content. I would say it already paid off. We are now 400 subscribers strong. Welcome to all the new folks! Let’s dive into some machine learning awesomeness!

The Latest Fashion

• Jeremy Howard wrote an excellent overview of how he reached the top 1 on a current kaggle competition with notebooks and videos!

• Want faster vector operations? Bolt compresses real-valued vectors and speeds up computation 10x.

• I shared prettymaps before, and here’s an interactive Streamlit app for easy usage. _{^{(tag @jesperdramsch on Twitter if you post some!)}}

Got this forwarded by a friend? Subscribe here!

the economy is taking a nose-dive, so let’s make sure we can do an extra-good job and be un-fireable for the foreseeable future with these awesome papers and libraries!

The Latest Fashion

• I enjoyed this paper about retrieving a meteorite fall with drones and machine learning!

• Regex is difficult and a bit old. Rulex tries to fix what wasn’t great about Regex and transpiles to Regex for maximum compatibility.

• Do you need data for tests, but bundling it in a Github repo is bad? Try Pooch to retrieve data for you!

My Current Obsession

I got really inspired by all the projects people presented at the ITU this week. So let’s carry over this excitement and dive right in:

The Latest Fashion

• Validating deep learning models can be complicated. Deepchecks provides a full suite (even on computer vision and tabular tasks) of checks to run against your system, including correlation and drift checks! Here’s the quickstart notebook.
• Lying with statistics is dangerous. But here are 6 ways people discredit valid statistical results and data science results without an actual basis.
• Testing Python code with production data can be a privacy nightmare. Faker is a package that generates believable but fake data for all your fake data needs.

My Current Obsession

I hope my Americans and Brits had a nice short week! I had five full days to collect some fantastic machine learning for you! Let’s go:

The Latest Fashion

• Computers that create realistic images from a text prompt seems like magic. Naturally, the new imagen is taking Twitter by storm, and there’s a Pytorch implementation.

• A new standardized metric library is on the block. From the forges of Huggingface, no less!

• Thought about trying Observable? Here’s a neat plot cheat sheet to get you started.

My Current Obsession

it was a 3-day week over here in Germany. I did some spring cleaning physically and digitally. So let’s explore some squeaky-clean machine learning awesomeness:

The Latest Fashion

• This AI learns traffic patterns from camera footage, making traffic jams a distant memory from the past.

• Models don’t always have to get bigger and badder, try the Efficient Deep Learning book instead.

• Aren’t we all curious why Deepmind loves Jax so much? Well here’s a Jax 101 tutorial.

My Current Obsession

I had a fairly frustrating week, dealing with things breaking and some migraines from the rapid weather changes. But that won’t keep us from some awesome machine learning, now does it? Here we go!

Also check out the new segment on data stories!

The Latest Fashion

• Deepmind was inspired by the successes of large language models lately, so they extended this innovation to reinforcement learning, introducing a general agent that can perform many different tasks out of the box.
• Pytorch is now ready to train on Mac M1 chipsets.
• Need a data visualization but the standard ones don’t quite fit? The Data Viz Project collects and lists visualization types for you to choose from.

the weather over here has been incredible this week, so I have been going out as much as possible. Additionally, I have started writing more again, which feels great. But let’s dive into our weekly machine learning:

The Latest Fashion

• Setting up Cuda on new architecture often is a nightmare, and cog is trying to solve this with pre-built containers for machine learning training
• Inspect intermediate layers of your Pytorch models with a little ML surgery without modifying the model code.
• Ever work with tabular data, this paper has done the work in comparing all machine learning models for your convenience.

My Current Obsession

coming live from the UK, I bring to you some fun machine learning!

The Latest Fashion

• Python in the browser? Not new. Including pandas, numpy or even folium? That’s PyScript and very new and exciting!

• Make pretty 3D visualizations in a oneliner from your keras model architecture with visualkeras.

• Google published a newer bigger Large Language Model. Their analysis of which improvements come from sheer size is insightful.

My Current Obsession

it’s been a long week back in the office after my week off. But I’m glad I had a few teleworking days saved up to get an easier transition. Regardless, let’s look at some learning machines!

The Latest Fashion

• I used to code telegram bots to send me ML training statistics on the go, with mlnotify you can do this in a single callback.
• This glossary of statistics jargon is a fantastic resource from Cassie Kozyrkov
• A new notebook competition for visualizations and some machine learning on Earth observation data was launched by EUMETSAT.

My Current Obsession

I’ve had a nice nature fix this week exploring the forests and hills around my home. But that shouldn’t keep us from some awesome machine learning!

The Latest Fashion

• Andrew Ng announced that the latest iteration of the Machine Learning Specialization, the course every ML practitioner took, is launching soon.

• The Stanford AI Index for 2022 was published with some interesting insights. Did you know the cost to train an image classifier is down 64%?

• Machine learning is a dual technology, yet, I was still surprised how AI drug discovery is turned into a bioweapon.

My Current Obsession

it was a nice short week here in Germany with a 4-day weekend coming in strong. Now, if just the clouds would disperse. But that doesn’t keep us from some awesome machine learning!

The Latest Fashion

• This Machine Learning Compendium is still in the making, but I’m excited about where it’s headed.

• Ever wonder if you could visually link Jupyter cells? I have, and PyFlow seems like an interesting attempt at this!

• Smaller ML models are important on the edge and in production. FasterAI is a library to help you accomplish smaller neural nets.

My Current Obsession

this week just blasted by me, barely enough time to sit down for a minute. So let’s dive into some recreational machine learning!

The Latest Fashion

• When you’re teaching machine learning, this Hugging Face 🤗  educational toolkit is great for understanding NLP
• Investigate your data with this clustering library for gaining insights.
• Remove personally identifiable data from your data set with Spacy’s scrubadub

My Current Obsession

isn’t Spring nice? The better weather and light outside is genuinely great for my mood. So are these machine learning links:

The Latest Fashion

• Pick up a free “draft” copy and all code of the book Probabilistic Machine Learning.

• This Twitter Thread by Aurélien Geron goes into his favourite parts of Python 3.x

• Midjourney is the latest image generation experiment, so try out the beta!

My Current Obsession

the weather outside is amazing, perfect timing for the weekend. But first let’s check out some awesome machine learning and Python links!

The Latest Fashion

• Bringing ConvNets to the 2020s went viral and now the code is released too!
• Automate your EDA and visualize your pandas DataFrames automatically with lux
• Explainable AI is all the rage, here’s a gentle introduction to Shapley values.

My Current Obsession

I’m back! Apologies for the one-week hiatus, but the anxiety around the current world got the better of me causing some health issues. Regardless, we have some great links (and things that might help if you too are suffering). Let’s do some machine learning!

The Latest Fashion

• This interactive exploration of transformer attention really helps understand the intricacies of transformers on language!

• TorchGeo is a Pytorch extension with datasets, transformations, and models for geospatial data

• The Deepmind podcast with Hannah Fry has started its second season!

My Current Obsession

Let’s ignore the news for 10 minutes and look at some machine learning together!

The Latest Fashion

• Encoding data is often the first step in a machine learning problem. Data2Vec promises to be efficient and work on speech, vision, and text data.

• All notebooks for the Python Data Science Handbook by Jake VanderPlas are openly available!

• EleutherAI have just openly released GPT-NeoX a 20 Billion parameter language model for free.

My Current Obsession

I’ve mostly been working behind the scenes this week. But that doesn’t stop us from some great machine learning resources!

The Latest Fashion

• Production data is the real test set, so check out Chip Huyens course material on data distributions shifts.

• Neural networks that turn Minecraft worlds into photo-realistic videos? Yes, please!

• Wonder how GPT works? The minGPT repo by Karpathy is low-key and educational.

My Current Obsession

Hey folks 🎉

between robots and a better view of Arxiv Preprints, I wrote a long piece about how I unscheduled my time to beat procrastination and reclaim my personal life.

My time as a PhD instilled a bit of an unhealthy imbalance, which I am now working on undoing. Please let me know what you think, as this is breaking the short form of this newsletter a bit. I’ll never break with the awesome links though, let’s go!

The Latest Fashion

Hey folks 🎉

I’m slowly getting my place ready to film and chill again, which is simply fantastic. But that distraction won’t stop us from some excellent machine learning!

The Latest Fashion

• Deepmind just published AlphaCode, an AI that can code competitively on an above-average human level.

• Not enough training data? Try SDV, the Synthetic Data Vault that brings different models for tables and time-series to the party!

• Do you write blog posts? This Python library can provide a bunch of stats about your writing, like the reading difficulty and average reading time.

Hey folks 🎉

I updated the ebook! Otherwise a bit slower week, but there’s lots of learning this week, let’s dive in:

The Latest Fashion

• Andrew Ng’s machine learning course is a classic, but it is in Matlab. Here’s the free Youtube version in Python of the Coursera course!

• Produce production-grade plots of neural network architectures. Where was this during my PhD?!

• Learn advanced Natural Language Processing with Spacy’s own course.

Hey folks 🎉

I’m currently unpacking boxes, but let’s unpack some great machine learning. I have also decided to answer last week’s Interview Question in this issue. Let me know what you think!

The Latest Fashion

• Last year OpenAI delighted everyone with an Avocado chair generated by DALL-E, but of course, the model is huge. In comes the smaller minDALL-E for your experimenting pleasure!

• It’s becoming more apparent that suitable ML applications are contingent upon clean labelled data. Doubtlab provides different methods to inspect noisy labels.

• Data scientists always wonder why someone would record written out numbers. The numerizer package can convert natural language numbers to ints and floats.

Hey folks 🎉

my computer is set up in my new flats and I’m hunting for a new couch and other furniture. But that doesn’t stop us from some amazing machine learning!

The Latest Fashion

• ConvNets for the 2020s is a new paper that shows little tweaks to CNNs to outperform transformers without using attention!

• I love improving science communication. This Latex package enables annotating equations within the document.

• PDFs about data science interviews are popular on Linkedin, now a book about deep learning interviews has made it to Arxiv for free.

Hey folks 🎉

I moved to Germany on New Year’s Day. Since everything in Germany works a bit slower, I will only get internet next week. But my limited consumption of awesome machine learning shall not hold us back. To the links!

The Latest Fashion

• Most Kagglers post their winning solutions but it can be difficult to sift through these posts. Lucky for us there’s a website aggregating solution posts!

• Rule-based learning can be extremely finicky but powerful and interpretable! Paypal open-sourced Iguanas for this application!

• Understanding transformers is essential for modern-day deep learning. Brandon Rohrer published a Transformers from Scratch post.

Hey folks 🎉

2022 is almost over. It had its highs for me, but I am SO ready for a new year. Thank you for being here, writing this newsletter has been a highlight every week!

You can start the year off with these awesome finds!

The Latest Fashion

Hey folks 🎉

it’s the festive season in the corner of my world, so almost everyone is on break now. Welcome to all the new people from Ian’s newsletter, glad to have you!

Let’s have some fun projects right on Christmas!

The Latest Fashion

Hey folks 🎉

this newsletter contains many things you can build yourself, but luckily this issue is already fully assembled.

The Latest Fashion

• I love playing around with Github Codepilot, but Huggingface 🤗 show you how to build your own Codeparrot🦜

• I shared the distill.pub intro to Graph Neural Networks before, and many have mentioned it was a bit confusing. This article tries to rectify this with the true introduction to GNNs for Novices.

• Regardless of whether you participate in Advent of Code, this error log from Matt Harrison is a genius idea that will increase your learning exponentially.

Hey folks 🎉

Today we have some fun festive art and some goodbyes in data science and I finally got back into some writing. So let's indulge!

The Latest Fashion

• Generative art is a ton of fun. Currently, Wombo Art is making the rounds on Twitter and it now has a Festive setting too. I'd love to see yours, I shared mine here.

• The chief editor of KDNuggets Gregory Piatetsky-Shapiro is stepping down after over 28 years of bringing data science insights to us. Not empty-handed but with extra nuggets in his personal history of KDNuggets.

• This keynote about scikit-learn by Gaël Varoquaux was very insightful (and only 20 minutes).

Hey folks 🎉

we back baby! Apologies for missing last week, I hope you can avoid the 2021 cold going around. But we have some great machine learning coming up and Advent of Code is back on too! Let's dive right in.

The Latest Fashion

• Time-series data can be tricky to deal with. TSAI implements regressors, classifiers and forecaster with a zoo of methods!

• Github projects and generally open-source tools can vary wildly in their quality. With Stethoscope you get a red-light green-light Chrome extension for repo health!

• At this point, everyone has seen the images with small Chihuahuas and blueberry muffins bamboozling both AI and humans. This dataset has a collection of naturally adversarial objects.