A股实时行情数据

Fetch China A-share stock market data (bars, realtime quotes, tick-by-tick transactions) via mootdx/TDX protocol. Use when working with Chinese stock data, mootdx library, TDX quotes, intraday minute bars, transaction history, or real-time A-share market data.

Helius API

Query Solana data via the Helius API. Use when the user asks about Solana wallet balances, token holdings, NFT holdings, transaction history, transfer activity, wallet identity/labels, wallet funding sources, parsing transactions, or other Solana on-chain data. Triggers on: "solana wallet", "sol balance", "solana transactions", "wallet history", "who funded this wallet", "wallet identity", "solana transfers", "solana NFTs", "helius", "check solana address", "solana data", "parse transaction", "e

What is Data Science @ O'reilly

_Data scientists combine entrepreneurship with patience, the willingness to build data products incrementally, the ability to explore, and the ability to iterate over a solution. They are inherently interdisciplinary. They can tackle all aspects of a problem, from initial data collection and data conditioning to drawing conclusions. They can think outside the box to come up with new ways to view the problem, or to work with very broadly defined problems: “here’s a lot of data, what can you make from it?”_

a very short history of #datascience

_The story of how data scientists became sexy is mostly the story of the coupling of the mature discipline of statistics with a very young one--computer science. The term “Data Science” has emerged only recently to specifically designate a new profession that is expected to make sense of the vast stores of big data. But making sense of data has a long history and has been discussed by scientists, statisticians, librarians, computer scientists and others for years. The following timeline traces the evolution of the term “Data Science” and its use, attempts to define it, and related terms._

Dataset Finder

Use this skill when users need to search for datasets, download data files, or explore data repositories. Triggers include: requests to "find datasets", "search for data", "download dataset from Kaggle", "get data from Hugging Face", "find ML datasets", or mentions of data repositories like Kaggle, UCI ML Repository, Data.gov, or Hugging Face. Also use for previewing dataset statistics, generating data cards, or discovering datasets for machine learning projects. Requires OpenClawCLI installatio

Free A Share Real Time Data

Fetch China A-share stock market data (bars, realtime quotes, tick-by-tick transactions) via mootdx/TDX protocol. Use when working with Chinese stock data, mootdx library, TDX quotes, intraday minute bars, transaction history, or real-time A-share market data.

Navigating Your Path to Becoming a Data Scientist

_Data science is one of the most in-demand careers today. With businesses increasingly relying on data to make decisions, the need for skilled data scientists has grown rapidly. Whether it’s tech companies, healthcare organizations, or even government institutions, data scientists play a crucial role in turning raw data into valuable insights. But how do you become a data scientist, especially if you’re just starting out? _

What is Data Science @ Quora

Data Science is a combination of a number of aspects of Data such as Technology, Algorithm development, and data interference to study the data, analyse it, and find innovative solutions to difficult problems. Basically Data Science is all about Analysing data and driving for business growth by finding creative ways.

How to Become a Data Scientist

_Data scientists are big data wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations._

Data Scientist Roadmap

_Data science is an excellent career choice in today’s data-driven world where approx 328.77 million terabytes of data are generated daily. And this number is only increasing day by day, which in turn increases the demand for skilled data scientists who can utilize this data to drive business growth._

Software Development Resources for Data Scientists

_Data scientists concentrate on making sense of data through exploratory analysis, statistics, and models. Software developers apply a separate set of knowledge with different tools. Although their focus may seem unrelated, data science teams can benefit from adopting software development best practices. Version control, automated testing, and other dev skills help create reproducible, production-ready code and tools._

Wikipedia

_Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data._