Machine Learning Weekly is a newsletter with over 8,000 subscribers about machine learning and deep learning, curated in spare time by @alirezasmr to accelerate research.
Every day, interesting machine learning projects get posted to GitHub, but they soon disappear into the abyss if you're not quick to bookmark them. I've created a small collection of ML projects that stood out to me from HN, reddit, and GitHub. Preference was given to open source projects witht an online demo. Let me know if I missed any!
Intersect Labs enables anyone to build and deploy machine learning models in 3 clicks, from any spreadsheet or database. Companies can make accurate predictions without bringing in a data scientist or ML engineer.
A demo inspired by the Tensorflow playground, but a bit broader in depth and with more customization.
Believe it or not, there was a period of time where not everything in Machine Learning was Deep Learning - and this site covers a good amount of traditional methods that are still quite relevant today.
Feedback is welcome!
Lionbridge’s 500,000+ annotators label your text, audio, image, and video data for machine learning. Using our custom-built platform, we can:🤖 Create chatbot training data🖼 Label images and video😍 Build sentiment analysis datasets👩💻 Source annotators from around the world💬 Improve machine translation
As students in high school, we realised that even though it is amazing, machine learning is really difficult to implement into projects.
To remove the hassle we faced ourselves, we created MLBlocks.
-Train models with only 50 images per class
-Create them without expensive GPUs
-Deploy on any platform through our API
-NO CODE REQUIRED