Data Engineering Zoomcamp is a free 9-week course on building production-ready data pipelines. Join the course here ππΌ
Benchmarking Knowledge Transfer in Lifelong Robot Learning
Collection of step-by-step playbooks for setting up AI/ML workloads on NVIDIA DGX Spark devices with Blackwell architecture.
Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.
Community-tested recipes, diagnostics, and benchmarks for CMP 170HX AI workloads
Evaluating and reproducing real-world robot manipulation policies (e.g., RT-1, RT-1-X, Octo) in simulation under common setups (e.g., Google Robot, WidowX+Bridge) (CoRL 2024)
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
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Deep learning for audio processing
Independent quantitative finance research project comparing U.S. and Kazakhstan equity markets using Python and portfolio theory.
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Public runnable examples of using John Snow Labs' NLP for Apache Spark.
Course Materials for Analytics in Stock Markets Zoomcamp
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI).
A free, self-paced 24-week AI engineering course: Python, machine learning, LLMs, RAG, fine-tuning, agents and MCP, Azure and Vertex and Bedrock, and Databricks. 43 runnable notebooks, one continuous case study. MIT licensed, no signup. By Zorost Intelligence AI Lab.
This is a Phi Family of SLMs book for getting started with Phi Models. Phi a family of open sourced AI models developed by Microsoft. Phi models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks
Multi-agent systems, memory, planning, reasoning loops
Bayesian optimisation & Reinforcement Learning library developed by Huawei Noah's Ark Lab
Hands-on Microsoft Fabric Data Science labs (FreshMart churn) with Thai study notes, PySpark/MLflow, and DP-604-aligned learning path.
SAMS - Scalable Agentic Market Simulator, a next gen AI finance automation paradigm, suitable for high frequency scenario while built for continuous learning and more sophisticated market simulation.
RadixQuantVLA is a unified, Lego-like framework for post-training quantization, benchmarking, and deployment preparation of Vision-Language-Action models, integrating QuantVLA, Omega-QVLA, OpenVLA, UniVLA, StarVLA, GR00T, and Pi0.5 routes with standardized launchers and validation on LIBERO benchmarks.
This is a repo with links to everything you'd ever want to learn about data engineering