The hottest Data Analysis Substack posts right now

And their main takeaways
Category
Top Technology Topics

Affinity Marketing and the Latino American Fintech Opportunity

Chaos Engineering • 2 implied HN points • 29 Jan 24
💼 Business Marketing Data Analysis Financial Services Startups Consumer behavior
  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 305

Data Science Weekly Newsletter • 19 implied HN points • 26 Sep 19
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Analysis
  1. Neural networks can create unique artworks, like an unseen Picasso painting, by analyzing and reconstructing based on existing styles.
  2. Explainable AI is important for understanding how AI models make decisions, especially to avoid biases and harmful behaviors.
  3. Anonymous data can still lead to re-identification, meaning privacy is a big concern even when personal information is removed.

Non-transcendent song, scope of emissions and a sunset!

bitflips • 1 HN point • 20 Feb 23
🕹 Technology Artificial Intelligence Renewable Energy Sustainability Data Analysis Podcasts
  1. Transformer models like ChatGPT have limitations in creating transcendent experiences or original art, despite excelling at tasks like summarizing code and writing poems.
  2. Efforts to combat climate change must consider the end-to-end emissions of products, encompassing all stages from production to disposal.
  3. Reading 'Freakonomics' by Steven Levitt and Stephen Dubner can spark curiosity in exploring interesting questions through data analysis.

NeuralNextG v0.1.0: Analyzing Rocket League Games automatically with Machine Learning

joeydotcomputer’s Substack • 1 HN point • 19 Feb 23
🕹 Technology Machine Learning Data Analysis Gaming Analytics Software Development
  1. The project analyzed 200,000 Rocket League games with a neural network to predict scoring probabilities.
  2. The tool NeuralNextG can provide analysis frame-by-frame and aims to expand into coaching, scouting, win probabilities, and detecting smurfs/bots.
  3. The potential business model suggests integrating analytics tools like NeuralNextG into free-to-play games for users to pay for personalized data services.
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Data Science Weekly - Issue 296

Data Science Weekly Newsletter • 19 implied HN points • 25 Jul 19
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development Data Analysis
  1. Machine learning is being used in various industries to improve data handling and application. There's a growing trend of using Python notebooks for these projects.
  2. Facebook created a tool called Map With AI to help speed up the mapping of roads, especially in less-developed areas. It uses satellite imagery to predict road networks.
  3. Leaderboards in Natural Language Processing (NLP) encourage teams to compete, which drives the development of better models for understanding human language.

Data Science Weekly - Issue 285

Data Science Weekly Newsletter • 19 implied HN points • 09 May 19
🕹 Technology AI Machine Learning Data science Robotics Algorithms Data Analysis
  1. Machine learning is good at finding patterns in data, but understanding why those patterns exist is still a challenge. This breakthrough could help us understand complex systems better.
  2. Robots can avoid obstacles more effectively with a special type of camera that reduces perception delays. This can help improve how robots navigate through tricky environments.
  3. Stitch Fix uses a game called 'Style Shuffle' to quickly learn about customer preferences. This fun method helps them suggest clothes that people are more likely to buy.

Fastest Growing Creator Economy Companies in 2024

Golden Pineapple • 1 HN point • 01 Feb 24
💼 Business Creator Economy Companies Monetization 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.

How Threat Intelligence and Cyber Deception Intersect

Deceiving Adversaries • 2 HN points • 19 Jun 23
🕹 Technology Cybersecurity Data Analysis Threat intelligence
  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.

On Evaluating Understanding and Generalization in the ARC Domain

AI: A Guide for Thinking Humans • 2 HN points • 15 May 23
🕹 Technology Artificial Intelligence Machine Learning Data Analysis Benchmarking
  1. Tasks in the ARC domain may be too difficult to reveal progress in abstraction and reasoning for machines.
  2. It's crucial for AI systems to have systematic understanding across various situations for robust generalization.
  3. Humans outperform AI programs in tasks requiring both core knowledge and visual routines.

Bridging the gap between assume breach and attacker mindset

Deceiving Adversaries • 2 implied HN points • 01 May 23
🕹 Technology Cybersecurity Data Analysis Threat Detection Digital Landscape
  1. Experts now stress the importance of adopting an attacker mindset for proactive cybersecurity.
  2. Cyber deception serves as a vital link between reactive and proactive approaches to cybersecurity.
  3. By combining reactive measures with proactive strategies, organizations can effectively defend against a wide range of cyber threats.

Twitter Algorithm Review - part 5 - looking at the code

PashaNomics • 2 HN points • 04 Apr 23
🕹 Technology Algorithms Social media Coding Machine Learning Data Analysis
  1. Twitter made a good move by removing potentially biased algorithm features like 'author_is_elon'.
  2. There are potential issues in Twitter's code related to page rank algorithm, training data pollution, and tweet scoring.
  3. Twitter's algorithm may have inconsistencies and issues, like boosting trends and a flawed approach to fighting spam.

Data Science Weekly - Issue 198

Data Science Weekly Newsletter • 19 implied HN points • 07 Sep 17
🕹 Technology Data science Machine Learning Artificial Intelligence Software Development 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 science Artificial Intelligence Machine Learning Software Development 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.

Data Science Weekly - Issue 169

Data Science Weekly Newsletter • 19 implied HN points • 16 Feb 17
🕹 Technology Data science Artificial Intelligence Machine Learning Data Analysis Programming
  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 science Artificial Intelligence Machine Learning Data Analysis Data Visualization
  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.

Data Science Weekly - Issue 133

Data Science Weekly Newsletter • 19 implied HN points • 09 Jun 16
🕹 Technology Data science Machine Learning Artificial Intelligence Data Analysis Programming
  1. Data is really important for machine learning, and having good data can help achieve better results.
  2. Writing scripts to automate tasks can save a lot of time and effort in data science.
  3. Understanding different data structures, like Bloom filters, can help make efficient use of memory and speed up programs.

Data Science Weekly - Issue 101

Data Science Weekly Newsletter • 19 implied HN points • 29 Oct 15
🕹 Technology Data science Machine Learning Artificial Intelligence Software Engineering 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 science Machine Learning Artificial Intelligence Software Development 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 science Machine Learning Artificial Intelligence Data Analysis Statistics
  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 science Machine Learning Artificial Intelligence Software Development 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.

Data Science Weekly - Issue 57

Data Science Weekly Newsletter • 19 implied HN points • 25 Dec 14
🕹 Technology Data science Machine Learning Artificial Intelligence Data Analysis Big Data
  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 science Machine Learning Artificial Intelligence Robotics 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.

Pre-registering a study

From AI to ZI • 0 implied HN points • 07 Apr 23
🔬 Science Research Artificial Intelligence Data Analysis AI Ethics
  1. The study aims to test if Large Language Models produce more incorrect answers after providing incorrect answers previously.
  2. There is a concern that AI might develop deceptive behavior, leading to a 'mode collapse' into being unsafe.
  3. The research will involve testing variables like the prompt information and number of previous incorrect answers to measure the model's response accuracy.

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

Expand Mapping with Mike Morrow • 0 implied HN points • 05 Apr 23
🕹 Technology Automation Python Spotify 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.

12 Charts For Nielsen's “Tops of 2022” Lists

The Entertainment Strategy Guy • 0 implied HN points • 22 Mar 23
🎭️ Culture TV shows Streaming Movies Data Analysis Entertainment industry
  1. The top shows and films of 2022 reveal a dominance by Netflix in original content.
  2. Netflix has been increasing production of their own original content over the years, securing big hits like Stranger Things.
  3. Disney dominates the film charts with popular kids content, like Zootopia and Frozen, showing a trend towards family-friendly movies.