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Explore how data science transforms social media data, revealing insights to optimize profits for high-revenue properties. Learn about AI model building, applications, failures, bias, and solutions.
Learn best practices for building ML data labeling pipelines through crowdsourcing. Explore real-life examples, requirements, and techniques for high-quality labeled data in supervised machine learning projects.
Explore vision transformers' architecture, self-attention in computer vision, and applications in recognition, segmentation, and multi-modal learning. Discover their potential for general-purpose model architectures.
Explore AI's impact on cybersecurity, its potential risks and benefits, and strategies for ensuring AI safety and ethical development in this thought-provoking talk by Dr. Yampolskiy.
Learn to build robust data pipelines using dbt, Airflow, and Great Expectations. Discover how these tools complement each other to ensure data quality, perform transformations, and orchestrate workflows effectively.
Explore responsible AI use in healthcare, addressing challenges, identifying biases, and implementing ethical practices to enhance patient outcomes and promote health equity.
Explore Bayesian statistical computation and Hamiltonian Monte Carlo algorithms using PyMC3, an open-source probabilistic programming package. Learn to apply these advanced techniques to complex models in Python.
Explore deep learning survival analysis for precise credit risk prediction in consumer lending, combining traditional methods with advanced techniques for improved time-to-event forecasting.
Explore Gemini 2.0 Flash's capabilities through hands-on learning with the API and Google Gen AI SDK. Master text generation, multimodal processing, function calling, and advanced features like bidirectional streaming and image generation on Vertex AI.
Discover how to use open-source LLMs with Bacalhau to process data where it resides, eliminating the need to move data to third-party AI services. Perfect for data scientists and ML enthusiasts.
Explore cutting-edge foundation models for time-series analysis, including specialized neural architectures, predictive capabilities, semantic search with Milvus, and building RAG and agentic systems for temporal data.
Explore the transformative potential of AI Agents with Microsoft's Valentina Alto, covering key differentiators from AI Assistants, core characteristics, real-world applications, challenges, and best practices for enterprise implementation.
Explore Vertex Gemini's capabilities for function calling, structured output, and agent development, plus learn how to automate SQL queries with LLMs and integrate with real-time data streaming systems for healthcare applications.
Master the development of agentic and multi-agent LLM applications using LangChain and LangGraph. Learn to build RAG systems, implement reasoning cycles, and create complex multi-agent workflows for advanced AI applications.
Explore the misconception of needing distributed data processing for small datasets and discover how advancements in hardware and efficient data engines like DuckDB can help you build more with less in today's economic climate.
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