ODSC - Open Data Science

MARCH 10, 2025

Walk away with practical approaches to designing robust evaluation frameworks that ensure AI systems are measurable, reliable, and deployment-ready. Explainable AI for Decision-Making Applications Patrick Hall, Assistant Professor at GWSB and Principal Scientist at HallResearch.ai

Data Scientist 52

Data Scientist Data Science LLM Machine Learning 52

Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

Explainable AI 52

Explainable AI Explainability Deep Learning Neural Network 52

ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Agentic AI DesignPatterns LLMs & RAG forAgents Agent Architectures &Chaining Evaluating AI Agent Performance Building with LangChain and LlamaIndex Real-World Applications of Autonomous Agents Who Should Attend: Data Scientists, Developers, AI Architects, and ML Engineers seeking to build cutting-edge autonomous systems.

Data Scientist 52

Data Scientist Machine Learning Large Language Models ML Engineer 52

Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. AI Engineer, Machine Learning Engineer, and Robotics Engineer are prominent roles in AI.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

The MLOps Blog

JUNE 27, 2023

Collaborative workflows : Dataset storage and versioning tools should support collaborative workflows, allowing multiple users to access and contribute to datasets simultaneously, ensuring efficient collaboration among ML engineers, data scientists, and other stakeholders.

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Machine Learning Metadata Data Scientist Data Quality 134

The MLOps Blog

AUGUST 11, 2023

At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. Model Training : Embeddings enable neural networks to consume training data in formats that extract features from the data. This is where embeddings come into play.

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ML Machine Learning Data Ingestion Deep Learning 52