The hottest Data Analysis Substack posts right now

And their main takeaways
Category
Top Technology Topics

How to hunt down TikTok's top videos

12challenges • 3 HN points • 13 Feb 24
🕹 Technology Data Analysis
  1. Hunting down TikTok's top videos is challenging because the data is not easily accessible through conventional methods like Google search.
  2. Using TikTok's Research API is limited and not helpful in obtaining the top TikTok videos by view count.
  3. Scraping TikTok's platform or using social monitoring tools are options to consider, but these methods come with challenges like legal implications and high costs.

Head of CIA OSINT emphasizes centrality of Twitter and Telegram surveillance

All-Source Intelligence Fusion • 4 HN points • 28 Sep 23
🇺🇸 U.S. Politics Data Analysis
  1. The head of CIA OSINT highlights the importance of surveillance on Twitter and Telegram for gathering open source intelligence.
  2. CIA's focus on AI technology has improved data analysis efficiency for vast amounts of surveillance data.
  3. The CIA incorporates controversial surveillance technologies like facial recognition and cellphone tracking data into their open source intelligence methodology.

The Data Quality Resolution Process

Data Products • 3 implied HN points • 11 Dec 23
🕹 Technology Data Analysis
  1. Stakeholders surface data quality issues, managers must balance responsiveness without burnout.
  2. Prioritize issues by determining urgency, impact, and potential solutions.
  3. Communicate clearly with technical stakeholders, implement fixes cautiously, and maintain trust through thorough communication.
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VSRF LIVE Tonight: Episode 150 - Santa Clara County Case Fatality Rate Analysis after C19 Vaccination

Steve Kirsch's newsletter • 1 implied HN point • 31 Oct 24
🏥 Health Politics Data Analysis
  1. The upcoming VSRF LIVE episode will discuss a study on the case fatality rate in Santa Clara County after COVID-19 vaccination. It suggests vaccinated residents might have a higher rate of death compared to those who are unvaccinated.
  2. The show aims to encourage open discussions about health data between the community and government agencies. The host has been actively participating in local public health events to share findings.
  3. Viewers are invited to watch the live episode and support the VSRF through donations. This support is crucial for keeping the show going and promoting health freedom.

Data Science Weekly - Issue 198

Data Science Weekly Newsletter • 19 implied HN points • 07 Sep 17
🕹 Technology Data Analysis
  1. Uber has developed a machine learning platform called Michelangelo that makes it easier for businesses to use AI and machine learning.
  2. Understanding how to evaluate models with imbalanced data sets is important for data scientists, specifically using precision, recall, or ROC metrics.
  3. Data journalism is evolving, and interviews with journalists and developers can reveal best practices for creating engaging digital stories.

Data Science Weekly - Issue 187

Data Science Weekly Newsletter • 19 implied HN points • 22 Jun 17
🕹 Technology Data Analysis
  1. Data from millions of social media photos can reveal important patterns about our clothing choices. This shows how useful data mining can be for understanding human behavior.
  2. Artificial intelligence is making strides in predicting mental health risks, like suicide. This can help save lives by allowing for timely interventions.
  3. Deep learning is useful for many different tasks, but developers often struggle to tune models. New approaches are being explored to simplify and improve the process.

Why Credit Card Data still makes money

Magis • 2 HN points • 03 Feb 24
💼 Business Data Analysis
  1. Credit card data remains valuable despite its availability because of the infrastructure and talent required to utilize it effectively.
  2. Having the computational resources and expertise to analyze consumer spending data gives larger firms an advantage over smaller firms.
  3. Success in leveraging consumer spending data depends on the rarity of talent that can understand and apply it effectively.

Affinity Marketing and the Latino American Fintech Opportunity

Chaos Engineering • 2 implied HN points • 29 Jan 24
💼 Business Data Analysis
  1. Affinity marketing involves targeting specific customer groups based on shared characteristics or interests.
  2. Hispanics in the US represent a large segment of the population, often working in labor-intensive jobs and having lower educational backgrounds and incomes.
  3. The Latino American fintech market presents an opportunity to provide financial services tailored to the needs of the Hispanic and Latino communities.

Data Science Weekly - Issue 169

Data Science Weekly Newsletter • 19 implied HN points • 16 Feb 17
🕹 Technology Data Analysis
  1. Longitudinal census data can help in predicting changes in neighborhoods, showing how data science can be applied to social issues.
  2. Deep learning is being used to develop new anticancer drugs, which demonstrates the potential of AI in medicine.
  3. There are many online resources to learn data science effectively, enabling individuals to create their own personalized learning paths.

Data Science Weekly - Issue 142

Data Science Weekly Newsletter • 19 implied HN points • 11 Aug 16
🕹 Technology Data Analysis
  1. Data analysis can be used to understand patterns, like analyzing tweets to see how they reflect someone's personality.
  2. Artificial intelligence is developing, but there are still limitations in how machines understand human language.
  3. Using technology like NASA imagery and machine learning can help improve agricultural predictions and trading.

Haystack 2024 - My Favorite Talks

Talking to Computers: The Email • 1 HN point • 09 Jul 24
🕹 Technology Data Analysis
  1. Retrieval Augmented Generation (RAG) is a hot topic this year, mixing search and text generation. It's being used in new and complex ways, even integrating images and tables.
  2. Vector and hybrid searches are also popular, combining traditional keyword searches with modern techniques for better results. This approach helps tailor searches more effectively.
  3. There were talks on various other topics, highlighting the importance of basics in search technology. Simple methods can still be very effective, especially for organizations trying to improve their search results.

Data Science Weekly - Issue 101

Data Science Weekly Newsletter • 19 implied HN points • 29 Oct 15
🕹 Technology Data Analysis
  1. Deep neural networks can identify various elements in images, showing their usefulness in both serious applications and fun experiments.
  2. Machine learning can be effectively used in practical applications like estimating delivery times, demonstrating its potential in real-world scenarios.
  3. There's an ongoing ethical debate about how self-driving cars should be programmed, particularly regarding their decision-making in life-and-death situations.

Data Science Weekly - Issue 96

Data Science Weekly Newsletter • 19 implied HN points • 24 Sep 15
🕹 Technology Data Analysis
  1. Job hunting in data science can be really stressful, even for the most confident candidates. It's important to talk about it and share experiences to help each other.
  2. Learning to find patterns in how data scientists work can make the job easier. This means using tools to enhance our own decision-making processes.
  3. When interviewing for data science roles, showcasing business knowledge is just as crucial as proving your technical skills. Understanding how data impacts businesses can set you apart.

Data Science Weekly - Issue 85

Data Science Weekly Newsletter • 19 implied HN points • 09 Jul 15
🕹 Technology Data Analysis
  1. PhD candidates often struggle to apply for data science jobs, but understanding industry expectations can help them succeed.
  2. AI tools are evolving quickly, with projects teaching machines to analyze and classify complex data, like galaxy images and social media content.
  3. There's a growing need for data scientists to address big issues, like obesity, by using available health data to create innovative solutions.

Data Science Weekly - Issue 62

Data Science Weekly Newsletter • 19 implied HN points • 29 Jan 15
🕹 Technology Data Analysis
  1. Machine learning is getting more important for businesses, especially as they deal with bigger data sets. Companies need to improve how they analyze data to stay competitive.
  2. A strong portfolio is key for landing a data science job. Showing off relevant skills in a well-organized way can really help you stand out to employers.
  3. Data science knowledge is becoming essential across different fields. Professionals are seeing high demand and good pay, making it a smart career choice for many.

How Threat Intelligence and Cyber Deception Intersect

Deceiving Adversaries • 2 HN points • 19 Jun 23
🕹 Technology Data Analysis
  1. Cyber Threat Intelligence provides insights into potential threats and helps organizations anticipate, detect, and respond effectively.
  2. Cyber Deception uses deceptive tactics to mislead attackers, acting as a proactive security approach.
  3. The combination of Cyber Threat Intelligence and Cyber Deception creates a powerful tool for organizations to detect, deter, and disrupt cyber threats, enhancing overall cybersecurity.

Data Science Weekly - Issue 57

Data Science Weekly Newsletter • 19 implied HN points • 25 Dec 14
🕹 Technology Data Analysis
  1. There are many great resources available to learn about data science. It can be helpful to start with recommended websites, books, and helpful tools.
  2. Data scientists are in high demand, with companies looking for specific skills like R, Python, and SQL. Knowing the right tools can give you an edge in getting a job.
  3. Big data is impacting various fields, including music and sports. Understanding how to analyze this data can lead to fresh insights and opportunities.

Data Science Weekly - Issue 36

Data Science Weekly Newsletter • 19 implied HN points • 31 Jul 14
🕹 Technology Data Analysis
  1. Robotics and deep learning are closely linked, as robots can benefit greatly from the data-driven training that deep learning provides. This connection could revolutionize how robots learn and operate.
  2. When learning data science, having advanced degrees isn't always necessary. There are steps you can take to prepare yourself for a data science career without a PhD.
  3. There is an explosion of public data available for research, like the Flickr Creative Commons dataset, which offers millions of images and videos. This is great for those looking to practice their data science skills.

Papers I've read this week

Artificial Fintelligence • 2 implied HN points • 05 Mar 23
🕹 Technology Data Analysis
  1. Routing improves performance of language models across all sizes
  2. Using agents to dynamically explore the internet could provide more data for training AI models
  3. LLaMa models have shown performance improvements compared to GPT-3, but the reasons behind these improvements are not fully clear

Fastest Growing Creator Economy Companies in 2024

Golden Pineapple • 1 HN point • 01 Feb 24
💼 Business Data Analysis
  1. The creator economy has experienced significant growth in recent years, evolving into a multi-billion dollar industry.
  2. Companies are playing a crucial role in supporting creators by providing various services like content creation tools, financial management, and analytics.
  3. Beehiiv and Patreon are leading the way in the creator economy, with impressive growth and popularity in the industry.

Bayesian A/B Testing

Boris Again • 1 HN point • 18 Apr 23
🔬 Science Data Analysis
  1. A/B testing compares two treatments to measure impact.
  2. Frequentist A/B testing involves hypothesis formulation, experiment design, and statistical testing.
  3. Bayesian A/B testing incorporates prior beliefs to estimate probabilities directly.

The Atlantis (Old 9:30 Club) Spotify Playlist Automation

Expand Mapping with Mike Morrow • 0 implied HN points • 05 Apr 23
🕹 Technology Data Analysis
  1. The author automated the process of creating a Spotify playlist featuring artists from a new music venue lineup in DC.
  2. They used Spotipy, a Python wrapper for the Spotify Web API, to compile songs from each artist's featured playlist.
  3. The biggest challenge faced during the process was getting the proper access code to work with the Spotify Web API.

Understanding Event-Driven Metrics

DevCube • 0 implied HN points • 05 Mar 23
🕹 Technology Data Analysis
  1. Event-driven systems have asynchronous actions and eventual consistency.
  2. Metrics are crucial for decision-making, monitoring, and predicting problems in the system.
  3. Metric design depends on the system component, targeting different aspects like user experience, system health, and usage statistics.

Research Report: Incorrectness Cascades

From AI to ZI • 0 implied HN points • 14 Apr 23
🕹 Technology Data Analysis
  1. Large Language Models may produce more incorrect answers if previous answers were incorrect
  2. The effect of incorrect previous answers on future answers is small and varies based on the prompt given to the AI
  3. Prompts that explicitly ask the AI to match previous behavior can lead to more incorrect answers