Difference between revisions of "Data Interoperability"
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|title=PRIMO.ai | |title=PRIMO.ai | ||
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| − | |keywords=artificial, intelligence, machine, learning, models | + | |keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools |
| − | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | + | |
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| − | [ | + | [https://www.youtube.com/results?search_query=ai+Data+Interoperability YouTube] |
| − | [ | + | [https://www.quora.com/search?q=ai%20Data%20Interoperability ... Quora] |
| − | [ | + | [https://www.google.com/search?q=ai+Data+Interoperability ...Google search] |
| + | [https://news.google.com/search?q=ai+Data+Interoperability ...Google News] | ||
| + | [https://www.bing.com/news/search?q=ai+Data+Interoperability&qft=interval%3d%228%22 ...Bing News] | ||
| − | * [ | + | * [[Data Science]] ... [[Data Governance|Governance]] ... [[Data Preprocessing|Preprocessing]] ... [[Feature Exploration/Learning|Exploration]] ... [[Data Interoperability|Interoperability]] ... [[Algorithm Administration#Master Data Management (MDM)|Master Data Management (MDM)]] ... [[Bias and Variances]] ... [[Benchmarks]] ... [[Datasets]] |
| + | * [[Data Quality]] ...[[AI Verification and Validation|validity]], [[Evaluation - Measures#Accuracy|accuracy]], [[Data Quality#Data Cleaning|cleaning]], [[Data Quality#Data Completeness|completeness]], [[Data Quality#Data Consistency|consistency]], [[Data Quality#Data Encoding|encoding]], [[Data Quality#Zero Padding|padding]], [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|augmentation, labeling, auto-tagging]], [[Data Quality#Batch Norm(alization) & Standardization| normalization, standardization]], and [[Data Quality#Imbalanced Data|imbalanced data]] | ||
| + | * [https://arrow.apache.org/ Apache Arrow] | ||
* [[Python#Pandas | Pandas]] provides an efficient implementation of a DataFrame | * [[Python#Pandas | Pandas]] provides an efficient implementation of a DataFrame | ||
* [[Creatives#Wes McKinney |Wes McKinney]] | * [[Creatives#Wes McKinney |Wes McKinney]] | ||
| − | a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient [[Analytics | analytic]] operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include [[Other Coding options#C/C++ | C/C++]], C#, [[Other Coding options#Go | Go]], [[Other Coding options#Java | Java]], [[JavaScript]], MATLAB, [[Python]], [[R Project]], Ruby, and Rust. | + | a cross-language [[development]] platform for in-[[memory]] data. It specifies a standardized language-independent columnar [[memory]] format for flat and hierarchical data, organized for efficient [[Analytics | analytic]] operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess [[Agents#Communication | communication]]. Languages currently supported include [[Other Coding options#C/C++ | C/C++]], C#, [[Other Coding options#Go | Go]], [[Other Coding options#Java | Java]], [[JavaScript]], MATLAB, [[Python]], [[R Project]], Ruby, and Rust. |
<youtube>7HiwzHWiF20</youtube> | <youtube>7HiwzHWiF20</youtube> | ||
Latest revision as of 22:40, 2 March 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Data Science ... Governance ... Preprocessing ... Exploration ... Interoperability ... Master Data Management (MDM) ... Bias and Variances ... Benchmarks ... Datasets
- Data Quality ...validity, accuracy, cleaning, completeness, consistency, encoding, padding, augmentation, labeling, auto-tagging, normalization, standardization, and imbalanced data
- Apache Arrow
- Pandas provides an efficient implementation of a DataFrame
- Wes McKinney
a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. It also provides computational libraries and zero-copy streaming messaging and interprocess communication. Languages currently supported include C/C++, C#, Go, Java, JavaScript, MATLAB, Python, R Project, Ruby, and Rust.
