github.com
Distributed decision tree ensemble learning in Scala.
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buildclub.ai
Build Club is a collaborative AI learning community. It runs the Campus program, which provides resources to learn, build and ship AI projects. The community offers AI-native courses, role-specific certifications and tracks for groups including young professionals, AI evangelists, solopreneurs and agencies. It is supported by AI companies.
github.com
CAMEL is an open-source community and framework for studying multi-agent systems at scale. It implements and supports various agents, tasks, prompts, models and simulated environments, and describes design principles including evolvability, scalability, statefulness and code-as-prompt.
github.com
cl-online-learning is a Common Lisp library collecting machine learning algorithms for online linear classification. It implements binary classifiers including Perceptron, AROW, SCW-I, logistic regression with SGD or ADAM, and FTRL-Proximal, plus multiclass approaches such as one-vs-rest, one-vs-one, multiclass AROW and softmax with FTRL-Proximal. Command line tools are provided as a roswell script, and the package is available from Quicklisp.
github.com
Implementation of Random Forest in Common Lisp.
university.clay.com
Claygent is Clay's AI web scraper used for enrichment in Clay. Unlike traditional enrichment providers that return static database results, it browses websites and reads pages to return insights, addressing last mile data that is too niche for data providers. Company enrichment requires a company domain, and people enrichment requires a LinkedIn profile URL.
github.com
Multidimensional cluster generation in Julia.
github.com
Multidimensional cluster generation in R.
github.com
Basic functions for clustering data: k-means, dp-means, etc.
github.com
Reinforcement Learning Coach by Intel® AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms.
cognitiveclass.ai
Cognitive Class AI by IBM is a free online learning platform. It offers over 100 courses, 300 hands-on projects and 20 learning paths covering AI, cloud computing, full-stack development, cybersecurity, data science and other technology fields. Learners can earn certificates and badges, and the platform serves over 3 million learners.
github.com
Neural networks, regression and feature learning in Clojure.
huggingface.co
Track 3: Agentic Demo Submission Hugging Face Agent Hackathon 2025.
github.com
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai.
prompthero.com
Where the pros learn the AI skills of the future. Explore your creativity with our hands-on AI courses.
github.com
Who wrote the tutorial of VQGAN+CLIP.
github.com
FANN (Fast Artificial Neural Network) binding.
cs231n.github.io
Course materials and notes for the Stanford class CS231n: Deep Learning for Computer Vision. The notes accompany the Stanford CS class and cover topics organized in modules. Spring 2026 assignments are listed.
github.com
cunn is a GitHub repository under the Torch organization that provides resources for the cunn project. The repository includes documentation for installation, usage, running unit tests, and GPU training concepts.
nirvacana.com
A blog post presenting a learning curriculum for becoming a data scientist, visualized as a metro map. The overall plan is organized progressively into areas or domains, each represented as a metro line with stations depicting topics.
github.com
cutorch is a CUDA backend for Torch7. It provides a torch.CudaTensor type that behaves like torch.FloatTensor with operations on the GPU, along with other GPU tensor types limited to copying, conversion, and certain indexing and shaping operations. The cutorch module offers functions for setting the GPU, reading device properties and memory usage, and managing streams and seeds.
utsouthwestern.edu
Search cardiology, angiology data collections and supporting datasets from USA.
dataschool.io
Data School is a blog about data science and machine learning. Its posts cover topics such as the difference between AI and machine learning, learning scikit-learn, AI progress, and using pandas for calculations. Posts are tagged by subject including Python, AI, and machine learning.
ryanswanstrom.com
Data Science 101 is a blog started in 2012 by Ryan Swanstrom about learning to become a data scientist. It covers getting started, data science career tips, free learning resources, videos, and academic papers.