Imagine you have a ton of data, but most of it isn't labeled. Even worse: labeling is very expensive. 😑
How can we get past this problem?
Let's talk about a different—and pretty cool—way to train a machine learning model.
☕️👇
Let's say we want to classify videos in terms of maturity level. We have millions of them, but only a few have labels.
Labeling a video takes a long time (you have to watch it in full!) We also don't know how many videos we need to build a good model.
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In a traditional supervised approach, we don't have a choice: we need to spend the time and come up with a large dataset of labeled videos to train our model.
But this isn't always an option.
In some cases, this may be the end of the project. 😟
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Here is a different approach: Active Learning.
Using Active Learning, we can have our algorithm start training with the data it has and interactively ask for new labeled data as it needs it.
Active Learning is a semi-supervised learning method.
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Here is the most important part of "Active Learning":
The algorithm will look at all the unlabeled data and will pick the most informative examples. Then, it will ask humans to label those examples and use the answers as part of the training process.
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Determining which examples are the most informative is the problematic part.
Worse case, we can select unlabeled examples randomly, but that wouldn't be smart.
The better the selection process is, the less data you'll need to build a model.
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When deciding, we want the algorithm to pick the most challenging examples for the model.
Here are some existing methods that you can research further:
1. Mojo 🔥 went open-source 2. Claude 3 beats GPT-4 3. $100B supercomputer from MSFT and OpenAI 4. Andrew Ng and Harrison Chase discussed AI Agents 5. Karpathy talked about the future of AI
...
And more.
Here is everything that will keep you up at night:
Mojo 🔥, the programming language that turns Python into a beast, went open-source.
This is a huge step and great news for the Python and AI communities!
With Mojo 🔥 you can write Python code or scale all the way down to metal code. It's fast!
The best real-life Machine Learning program out there:
"I have seen hundreds of courses; this is the best material and depth of knowledge I've seen."
That's what a professional Software Engineer finishing my program said during class. This is the real deal.
I teach a hard-core live class. It's the best program to learn about building production Machine Learning systems.
But it's not a $9.99 online course. It's not about videos or a bunch of tutorials you can read.
This program is different.
It's 14 hours of live sessions where you interact with me, like in any other classroom. It's tough, with 30 quizzes and 30 coding assignments.
Online courses can't compete with that.
I'll teach you pragmatic Machine Learning for Engineers. This is the type of knowledge every company wants to have.
The program's next iteration (Cohort #8) starts on November 6th. The following (Cohort #9) on December 4th.
It will be different from any other class you've ever taken. It will be tough. It will be fun. It's the closest thing to sitting in a classroom.
And for the first time, the next iteration includes an additional 9 hours of pre-recorded materials to help you as much as possible!
You'll learn about Machine Learning in the real world. You'll learn to train, tune, evaluate, register, deploy, and monitor models. You'll learn how to build a system that continually learns and how to test it in production.
You'll get unlimited access to me and the entire community. I'll help you through the course, answer your questions, and help with your code.
You get lifetime access to all past and future sessions. You get access to every course I've created for free. You get access to recordings, job offers, and many people doing the job you want to do.
No monthly payments. Ever.
The link to join is in the attached image and in the following tweet.
The link to join the program:
The cost to join is $385.
November and December are the last two iterations remaining at that price. The cost will go up starting in January 2024.
Today, there are around 800 professionals in the community.ml.school
Live sessions and recordings:
Sessions are live, and I recommend every student to attend if they can.
But we also record every session, and you get access to the recordings. You can watch them whenever you want.
We also have 2 office hours. They are optional but a lot of fun!