Best AI tools for< Tableau Developer >

Tableau is a visual analytics platform that helps people see, understand, and act on data. It is used by organizations of all sizes to solve problems, make better decisions, and improve operations. Tableau's platform is intuitive and easy to use, making it accessible to people of all skill levels. It also offers a wide range of features and capabilities, making it a powerful tool for data analysis and visualization.

Tableau Augmented Analytics is a class of analytics powered by artificial intelligence (AI) and machine learning (ML) that expands a human’s ability to interact with data at a contextual level. It uses AI to make analytics accessible so that more people can confidently explore and interact with data to drive meaningful decisions. From automated modeling to guided natural language queries, Tableau's augmented analytics capabilities are powerful and trusted to help organizations leverage their growing amount of data and empower a wider business audience to discover insights.

Lucia, the AI-powered management reporting software created by Board Intelligence, helps you craft brilliantly clever and beautiful management reports that spur your business to action. Lucia's AI-powered nudges ensure your team links to your organization's big picture, avoids blind spots in your analysis and plans, and delivers insights you can act on. Lucia's smart AI-powered editing tools help your team refine and land their message: Cut the word count and make reports easier to read with Lucia's Simplify and Make Concise tools. Auto-Summarization builds powerful executive summaries that put the key points up front. Build papers around Question Driven Insight™, a methodology proven to stimulate critical thinking that your business will act on. Guided by Lucia's smart templating system, your management team can focus their reports on the questions you want them to grapple with — the ones that shift the needle. Well-visualized and timely data can be powerful. Lucia, our management reporting platform, unlocks this with Tableau and PowerBI integrations that link real-time data dashboards directly into your papers. Papers created in Lucia are eye-catching, consistent, and easy-to-digest — no design skills required. Lucia also integrates video into reports, helping your management team to bring their messages to life.

hongbomiao.com is a personal research and development (R&D) lab that facilitates the sharing of knowledge. The repository covers a wide range of topics including web development, mobile development, desktop applications, API servers, cloud native technologies, data processing, machine learning, computer vision, embedded systems, simulation, database management, data cleaning, data orchestration, testing, ops, authentication, authorization, security, system tools, reverse engineering, Ethereum, hardware, network, guidelines, design, bots, and more. It provides detailed information on various tools, frameworks, libraries, and platforms used in these domains.

Fueling-Ambitions-Via-Book-Discoveries is an Advanced Machine Learning & AI Course designed for students, professionals, and AI researchers. The course integrates rigorous theoretical foundations with practical coding exercises, ensuring learners develop a deep understanding of AI algorithms and their applications in finance, healthcare, robotics, NLP, cybersecurity, and more. Inspired by MIT, Stanford, and Harvard’s AI programs, it combines academic research rigor with industry-standard practices used by AI engineers at companies like Google, OpenAI, Facebook AI, DeepMind, and Tesla. Learners can learn 50+ AI techniques from top Machine Learning & Deep Learning books, code from scratch with real-world datasets, projects, and case studies, and focus on ML Engineering & AI Deployment using Django & Streamlit. The course also offers industry-relevant projects to build a strong AI portfolio.

Awesome MLOps is a curated list of tools related to Machine Learning Operations, covering areas such as AutoML, CI/CD for Machine Learning, Data Cataloging, Data Enrichment, Data Exploration, Data Management, Data Processing, Data Validation, Data Visualization, Drift Detection, Feature Engineering, Feature Store, Hyperparameter Tuning, Knowledge Sharing, Machine Learning Platforms, Model Fairness and Privacy, Model Interpretability, Model Lifecycle, Model Serving, Model Testing & Validation, Optimization Tools, Simplification Tools, Visual Analysis and Debugging, and Workflow Tools. The repository provides a comprehensive collection of tools and resources for individuals and teams working in the field of MLOps.

The Data Scientist Roadmap2024 provides a comprehensive guide to mastering essential tools for data science success. It includes programming languages, machine learning libraries, cloud platforms, and concepts categorized by difficulty. The roadmap covers a wide range of topics from programming languages to machine learning techniques, data visualization tools, and DevOps/MLOps tools. It also includes web development frameworks and specific concepts like supervised and unsupervised learning, NLP, deep learning, reinforcement learning, and statistics. Additionally, it delves into DevOps tools like Airflow and MLFlow, data visualization tools like Tableau and Matplotlib, and other topics such as ETL processes, optimization algorithms, and financial modeling.

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

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