The hottest Data Analysis Substack posts right now

And their main takeaways
Category
Top Technology Topics

Prompt Engineering with GPT-4: Charting and Mapping European Tourism Trends

Data at Depth • 19 implied HN points • 11 Apr 24
🕹 Technology Data Analysis Data Visualization Artificial Intelligence Programming Web Development
  1. Efficiency is highly sought after state of being for coders and data analysts. GPT-4's Code Interpreter functionality significantly streamlines the process of transforming CSV data into data visualizations.
  2. GPT-4 can generate Python code for various types of data visualizations like line charts, bar charts, and area charts. Simply prompting GPT-4 with specific information can quickly produce comprehensive visualizations.
  3. GPT-4 can be utilized to filter datasets, analyze trends, and create innovative visual representations like choropleth maps. Incorporating GPT-4 into data analysis workflows can lead to faster and efficient results.

Data at Depth Newsletter 4 - Consistency in Creating & GPT-4's Custom Instructions Tool

Data at Depth • 39 implied HN points • 11 Jan 24
🕹 Technology Data Analysis Coding AI
  1. Consistency is crucial for success, according to top creators. It's important to maintain consistency even during challenging times.
  2. Data at Depth newsletter is reader-supported. Consider subscribing to receive new posts and support the author's work.
  3. Get a 7-day free trial to access the full post archives of Data at Depth by subscribing.

Evaluating LLM Agents and Applications

LLMs for Engineers • 79 implied HN points • 11 Jul 23
🕹 Technology AI Development Machine Learning Software Engineering Data Analysis
  1. Evaluating large language models (LLMs) is important because existing test suites don’t always fit real-world needs. So, developers often create their own tools to measure accuracy in specific applications.
  2. There are four main types of evaluations for LLM applications: metric-based, tools-based, model-based, and involving human experts. Each method has its strengths and weaknesses depending on the context.
  3. Understanding how well LLM applications are performing is essential for improving their quality. This allows for better fine-tuning, compiling smaller models, and creating systems that work efficiently together.

Taking time series modeling and stream processing mainstream

Gradient Flow • 139 implied HN points • 10 Nov 22
🕹 Technology Data Analysis Machine Learning Open Source Podcasts Tools
  1. The global market for time series analysis software is growing significantly, presenting opportunities for companies and startups
  2. There is a need to focus on stream processing to gain competitive advantages in making quick decisions and leveraging incoming data
  3. Open source tools and collaborations play a key role in advancing fields like time series modeling and stream processing
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Data Deep Dive: Predicting China's Exports Using AIS Vessel Tracking Data (+ Other Uses)

The Data Score • 59 implied HN points • 28 Jun 23
🕹 Technology Data Analysis Risk management Supply Chain
  1. AIS vessel tracking data can predict China's exports, monitor global trade, and understand real-time economic activity.
  2. Data cleansing is crucial for turning raw AIS data into actionable insights. Cleaning the data involves filtering out anomalies and ensuring accuracy.
  3. It's important to consider limitations like the exclusive focus on large commercial ships, uncertainties in cargo data, and vessel behavior anomalies when analyzing AIS data.

Address Not Found (Part 2)

Cybernetic Forests • 59 implied HN points • 18 Jun 23
🕹 Technology AI Communication Media Data Analysis
  1. Communication technologies historically categorized into one-to-one, one-to-many, and many-to-many transmission systems.
  2. Artificial Intelligence operates in a unique structure called many-to-one-to-one, where data from multiple sources shapes responses for individual users.
  3. AI systems, despite the appearance of one-to-one engagement, actually function asynchronously and as a blend of many-to-one transmission, controlled by the operators and designers.

The Bull Case for Alternative Data

The Data Score • 59 implied HN points • 11 Apr 23
💰 Finance Investing Data Analysis Financial Markets ROI Network Effects
  1. The Alternative Data industry is currently facing challenges but has the potential for long-term success by emphasizing clear client outcomes and building network effects.
  2. Understanding the value clients gain from data insights is crucial, as insights drive decisions and financial outcomes.
  3. Creating network effects and aligning data teams with critical client outcomes are key factors for the Alternative Data industry to move towards sustained growth and productivity.

Is ChatGPT Getting worse? A Case Study on Confirmation Bias

The Data Score • 59 implied HN points • 20 Jul 23
🕹 Technology AI Machine Learning Data Analysis
  1. Testing and improving AI models, like ChatGPT, is crucial as our reliance on AI grows. Ensuring model performance and explainability is key for professionals in the field.
  2. Machine learning and AI models face challenges with explainability, especially in the context of large language models like ChatGPT. Specific wording and temperature settings can greatly impact model outputs.
  3. Confirmation bias is a common human tendency to search for and interpret information that aligns with existing beliefs. It's important to recognize and manage biases when assessing AI model performance.

Microsoft Sentinel SOC 101: How to Detect and Mitigate Drive-by Download Attacks with Microsoft Sentinel

Rod’s Blog • 59 implied HN points • 04 Oct 23
🕹 Technology Cybersecurity Software Data Analysis Incident Response Network Security
  1. Drive-by download attacks exploit vulnerabilities to download malicious code without user knowledge. They can lead to data breaches and install malware.
  2. Mitigation strategies include user education, enforcing security policies, monitoring network traffic, and using SIEM services like Microsoft Sentinel.
  3. Microsoft Sentinel can help detect drive-by download attacks by collecting relevant data, enriching it, analyzing with rules and ML, visualizing results, and automating incident response.

18 months since - funding statistics for the 2021 space startup cohort

Intersections (by Filip) • 59 implied HN points • 17 Aug 23
🕹 Technology Space Startups Finance Investments Data Analysis
  1. Raw data reveals the financial landscape of space startups in 2021, with significant amounts invested and patterns in subsequent funding rounds.
  2. Data collection discrepancies highlight the importance of a diverse dataset and the impact of subsequent funding on company growth and investor interest.
  3. Understanding the timeline of funding, company failures, loyal investors, and the need for continuous rounds sheds light on the complexities and challenges faced by space startups.

The Paradox of Finding Surprising Insights in Alternative Data

The Data Score • 59 implied HN points • 22 Jun 23
💼 Business Data Analysis Investment Financial Markets Market research Risk management
  1. Institutional investors need to find surprising insights in data but also be skeptical of them to ensure accuracy and avoid errors.
  2. When using alternative data to make predictions, it's crucial to verify if the insights answer the right questions and differ from the market consensus.
  3. Digging into the data through various methods like independent validation, error margin assessment, and data integrity checks is essential for investors to ensure the reliability of surprising insights.

Data used in nuclear war piece

Myth Pilot • 58 implied HN points • 26 Apr 23
🕹 Technology Data Analysis Simulation
  1. The author wanted to understand the impact of a theoretical nuclear war on voter demographics
  2. Access to geographic data by locality required decoding binary files from a game simulator
  3. To access specific data for research, the author wrote a script to extract the needed information

The Future of Network Observability and Network Automation

Internet Dynamics • 58 implied HN points • 06 Sep 23
🕹 Technology Networking Observability Automation Data Analysis APIs
  1. Network observability is crucial for network automation to handle real-time mitigation and remediation.
  2. Observability solutions need to consider topology, alerts, correlation, suppression, policy, and meta-data for effective network monitoring.
  3. Future approaches to observability and automation should recognize and manifest common components like Topology, CMDBs and Meta-data.

Vulnerability Management and Developer Toil

Resilient Cyber • 119 implied HN points • 02 Apr 23
🕹 Technology Cybersecurity Vulnerabilities Software Developers Data Analysis
  1. Vulnerability management is crucial for security but often overwhelms developers with too much information. It’s important to focus on vulnerabilities that really pose a risk, instead of just following strict checklists.
  2. The number of vulnerabilities has exploded in recent years, but most are never exploited. Organizations need better ways to prioritize which vulnerabilities to address based on actual risk, rather than just severity scores.
  3. Security teams should work more closely with developers to reduce friction and support their efforts. Improving communication and providing context can make security a partner, not a blocker.

GPT-4 Doesn't Have "Gender Bias." It's Just Bad At Language (Still)

jonstokes.com • 154 implied HN points • 18 May 23
🕹 Technology Artificial Intelligence Software Language processing Engineering Data Analysis
  1. Different approaches to evaluating AI performance have practical implications in development, deployment, and regulation.
  2. Language models like GPT-4 struggle with resolving ambiguity in human language due to limitations in understanding context.
  3. Using an engineering approach, providing relevant context, and improving language parsing can help mitigate language model biases and inaccuracies.

Synthesizing Introspection: The AI Mediated Self

Cybernetic Forests • 99 implied HN points • 04 Dec 22
🕹 Technology AI Ethics Self-care Artificial Intelligence Data Analysis
  1. The challenge of using AI for introspection is knowing what you are really asking and understanding the limitations of the technology.
  2. Conversing with AI to simulate interactions with younger versions of oneself may not provide personalized or beneficial insights.
  3. Relying on AI for deep introspection or personal growth may present risks of misunderstanding, projection, and avoidance of true self-care.

The KQL Mysteries: The Holiday 2023 Episode Part 3

Rod’s Blog • 39 implied HN points • 13 Dec 23
🕹 Technology Cybersecurity Data Analysis
  1. The mysterious numbers given by the hacker were not random, but dates with a hidden significance, leading to a revelation about impending events.
  2. Through identifying patterns in network traffic using KQL, Jon and Sarah uncovered a hacker exploiting a security vulnerability and resolved to apply a critical patch.
  3. The duo set a trap to stop the hacker's planned attack, showcasing the importance of proactive security measures in monitoring and defending against cyber threats.

The KQL Mysteries: The Holiday 2023 Episode Part 2

Rod’s Blog • 39 implied HN points • 12 Dec 23
🕹 Technology Cybersecurity Coding Data Analysis
  1. The hacker in the story had a personal connection to one of the characters, making the situation more intense and personal.
  2. Using Kusto Query Language (KQL), the characters tried to analyze the hacker's network traffic and database activity to uncover clues about the hacker's identity and location.
  3. Despite challenges in decoding the hacker's data, the characters discovered a message from the hacker in the database logs, prompting them to solve a mysterious puzzle involving numbers.

Why you should analyze the distribution of your Data [Math Mondays]

Technology Made Simple • 59 implied HN points • 14 Mar 23
🕹 Technology Data Analysis Math Software Engineering Modeling Statistics
  1. Analyzing the distribution of your data is crucial for accurate analysis results, helps in choosing the right statistical tests, identifying outliers, and confirming data collection systems.
  2. Common techniques to analyze data distribution include histograms, boxplots, quantile-quantile plots, descriptive statistics, and statistical tests like Shapiro-Wilk or Kolmogorov-Smirnov.
  3. Common mistakes in analyzing data distribution include ignoring or dropping outliers, using the wrong statistical test, and not visualizing data to identify patterns and trends.

k-Core Decomposition

Graphs For Science • 52 implied HN points • 24 Feb 24
🔬 Science Graph Theory Algorithms Data Analysis
  1. k-Core Decomposition is a way to explore the structure of networks by identifying the largest subgraph where every node has a specified minimum degree.
  2. The k-Core Decomposition algorithm involves recursively removing nodes with degrees lower than a specified threshold to reveal the k-core and k-shell structure of a graph.
  3. The degree of a node in a k-core doesn't have an upper limit, providing unique insights into network connectivity beyond traditional degree-based analysis.

How do AI security products being sold to schools really work?

School Shooting Data Analysis and Reports • 19 implied HN points • 12 Mar 24
🕹 Technology AI Security Education Data Analysis
  1. School administrators are facing pressure to evaluate AI security products but may lack expert knowledge to do so.
  2. Understanding how AI models are trained, the probability threshold, and error rates are crucial when assessing AI security solutions.
  3. The high stakes of AI security decisions for schools underscore the importance of asking detailed questions about the technology being implemented.

Official Czech Republic record level data released Nov 2024 confirms Moderna has nearly 50% higher ACM than Pfizer

Steve Kirsch's newsletter • 10 implied HN points • 19 Jan 25
🏥 Health Politics Vaccine Safety Public Health Epidemiology Government Policy Data Analysis
  1. The Czech Republic has released detailed vaccine data for the first time, showing that the Moderna vaccine may be more dangerous than the Pfizer vaccine. This data is important for understanding vaccine safety.
  2. Analysis of this data suggests that the Moderna vaccine could increase all-cause mortality by about 50% compared to Pfizer, which raises serious concerns about its safety even outside of COVID periods.
  3. Despite this significant information available, it appears that many in the medical community are ignoring the findings, which highlights the need for more transparency in public health data.

How to use Machine Learning for your Small Business [Storytime Saturdays]

Technology Made Simple • 79 implied HN points • 17 Dec 22
🕹 Technology Machine Learning Small business AI Data Analysis Implementation
  1. Machine Learning can be effective for small businesses too, not just large corporations, opening up opportunities for growth and innovation.
  2. Understanding the process of implementing AI can benefit professionals across various roles, not just those directly working in AI fields.
  3. Having the right skills and knowledge about AI implementation can significantly increase your chances of success and career advancement.

Lateral thinking

Logging the World • 79 implied HN points • 12 Nov 22
🔬 Science Research Data Analysis Public Health Epidemiology Testing
  1. Lateral flow tests had a much lower false positive rate than many initially assumed, around 0.03%, showing their effectiveness.
  2. Data on PCR retests of positive lateral flow tests revealed a positive predictive value of 82% even at low prevalence, supporting the reliability of lateral flow tests.
  3. A rise in prevalence due to variants like delta and omicron, as well as ease in lockdown restrictions, contributed to the wider acceptance of lateral flow tests for controlling the pandemic.

Modifying readability with large language models (pt. 1)

The Counterfactual • 19 implied HN points • 29 Feb 24
🕹 Technology AI Readability Language Models Human-computer interaction Data Analysis
  1. Large language models can change text to make it easier or harder to read. It's important to check if these changes actually help with understanding.
  2. By comparing modified texts to their original versions, it's clear that 'Easy' texts are generally simpler than 'Hard' texts. However, it can be harder to make texts significantly simpler than they originally are.
  3. Despite the usefulness of these models, they might sometimes lose important information when simplifying texts. Future studies should involve human judgments to see if the changes maintain the original meaning.

The latest round in the $2M debate

Steve Kirsch's newsletter • 8 implied HN points • 25 Jan 25
🏥 Health Politics Public Health Vaccination Policy Debate Data Analysis Risk Assessment
  1. The vaccines may have caused more COVID cases and deaths than they helped prevent. Data shows that vaccinated individuals had higher case rates during 2021 and 2022.
  2. Some studies suggest that vaccines may increase the risk of adverse health outcomes, like myocarditis and all-cause mortality, especially with certain brands.
  3. There is ongoing debate and skepticism surrounding vaccine safety, with some polls indicating that a significant number of people believe vaccines have contributed to deaths similar to COVID itself.

Clare Craig Analysis of U.S. Data: It's All Healthy User Bias

Rounding the Earth Newsletter • 8 implied HN points • 22 Jan 25
🏥 Health Politics COVID-19 Vaccine Policy Public Health Data Analysis
  1. The concept of Healthy User Bias (HUB) suggests that healthy people are more likely to get vaccinated, which can skew vaccine effectiveness data.
  2. Recent COVID-19 data trends show a pattern where states are experiencing similar mortality rates, indicating a connection between health factors and vaccination rates.
  3. Deaths related to despair, like suicide and drug use, appear to be affecting mortality rates, especially in poorer areas, alongside any potential vaccine-related deaths.