Eric Schmalzbauer’s Post

Worth reading if you deal with large, streaming data sets. #ObsessivelyEnthusiasticInvestor at REFASHIOND Ventures: The Industrial Transformation Fund.

All due respects LangChain is highly overrated. if you want to understand the naunxed differences between models it best to work against individual models https://lnkd.in/e7mqckhM

Thirteen Web3 Companies Unify Crypto Data With a Single Platform, jQuery Project https://lnkd.in/d3i47JPX #informationtechnology #newsmedia #itdigest #news #fintech #QuickNode #SubQuery #BitQuery #DappLooker

🤝 New partnership alert 🤝 #Polkadex and #THEA will harness the power of SubQuery's data indexer for efficient retrieval of on-chain data! 📰 Get all the details below 👇

Dipping my toes in stock and crypto price prediction to learn how to use models in my future crypto trading app. I used Neural Prophet to predict BTC-USD prices for the next couple of days (the blue line) based on previous 36-hour data. I'm still new to this, have done some data science before. Setup my neural model to use the "AdamW" optimizer and nChangepoints to 410, the rest is all default settings.

👥 Introducing the ‘Cohort analysis’ data set 👥 What? More powerful user activity data in the form of monthly user cohort tables. Why? In addition to aggregate DAU, WAU, and MAU figures, it’s insightful to track user retention and churn separately for users that become customers of a protocol at different points in time. So what? For example, we might find that traders who started to use Uniswap two years after the protocol’s launch are more engaged (higher retention) than its initial users, as a result of better liquidity and asset availability (network effects) later on.

Great explaining how LangChain agents use chain of thought prompting using LLM reasoning engine to think like a human in executing series of actions without human intervention. https://lnkd.in/gGmbjRsR

The presented plot offers a comprehensive overview of Bitcoin's (BTC-USD) price dynamics throughout the year 2023. The data has been meticulously filtered to exclusively encompass entries from 2023 onwards, providing a focused and detailed examination of this specific timeframe. The primary element of the visualization is the solid blue line, which graphically represents the actual closing prices of Bitcoin. This line encapsulates the inherent volatility and fluctuations in the market, offering a visual narrative of Bitcoin's day-to-day performance. Complementing the actual prices are two strategically incorporated dashed lines, portraying the 7-day and 30-day Simple Moving Averages (SMAs). These moving averages serve as invaluable analytical tools, smoothing out the raw price data and unveiling underlying trends and potential turning points within the market. As the actual closing prices interact with these moving averages, observable patterns emerge, providing insights into the prevailing market sentiment. Crossings above or below the SMAs can signal shifts in trend direction, making the plot a useful resource for technical analysis and decision-making. The title "BTC-USD Close Prices with SMAs Over Time (2023)" succinctly encapsulates the plot's focus, while the axis labels "Date" and "Close Price" provide clarity regarding the plotted data. The legend further demystifies the visual elements, attributing each line to its corresponding representation. In summary, this visualization serves as a powerful tool for traders and analysts, facilitating the identification of trends and potential signals in the Bitcoin market during the specific time span of 2023. If you'd like to learn how to create plots like this! Grab a copy of "Machine Learning in Python for Everyone" @ https://lnkd.in/esZaV7ZX #machinelearning #ai #chatgpt #datascience #dataanalytics #datavisualization #learning #innovation

In this exciting era of technological advancement, Stock Market APIs empower individuals to stay ahead in the ever-changing financial landscape. Whether you're a seasoned investor, a quant enthusiast, or a developer with a passion for finance, embracing Stock Market APIs is a transformative step towards gaining valuable insights and seizing opportunities in the dynamic world of stocks and trading. Here are the top 6 Stock Market APIs you should know about: 🌐 StockNews API The StockNews API is a comprehensive platform that delivers real-time and historical financial news data. It provides access to various news sources, including mainstream media and financial publications. 🌐 Polygon io API  Polygon io offers a robust stock market API with real-time and historical market data, including stock quotes, trades, and financials. Their RESTful API allows developers to access tick-level data, historical stock prices, and intraday data. 🌐 Bloomberg API  Bloomberg, a leader in financial data and analytics, provides a comprehensive API for accessing their vast repository of financial information. The Bloomberg API offers real-time and historical market data, company fundamentals, economic indicators, etc.   🌐 Intrinio API  The Intrinio API offers a wide range of financial data, including stock prices, company fundamentals, and economic data. With a user-friendly interface, developers can quickly access financial statements, historical stock prices, and news articles. 🌐 Alpaca API  Alpaca provides an API explicitly designed for algorithmic trading and market data. It offers commission-free trading and access to real-time market data, historical bars, and account information.  🌐 IEX Cloud API  IEX Cloud offers a comprehensive and user-friendly API for accessing financial market data with a vast range of data points, including real-time and historical stock prices, company financials, economic indicators, and more. To learn more about such exciting APIs, follow Fyrii. #StockMarketAPIs #FinancialData #InvestmentDecisions #DataDrivenFinance #EmpoweringTraders