Gina Acosta

Understanding Data Science: A Guide to Key Techniques 👇

#datascience #python #machinelearning #MLSky

Thanks for sharing, Javier! Obrigada!

Ohh okay 😂

Thank you! 😊
Maybe it’s time for me to learn Greek, btw do you also speak Spanish?

Followed you with my two accounts, the newest one is to share more about my ventures and connect with tech people and tech founders :)

I don't know how I didn't notice that tab before, thanks for the tip!

Thank you! What is your X user? So I can follow back :) For growth in BSky I'm trying using hashtags related to the content I post. Still trying to figure out how this platform works

Interesting, how does starter packs work?

Thanks for sharing! 😊

a close up of a pikachu with red cheeks looking at the camera ALT: a close up of a pikachu with red cheeks looking at the camera

All done! Thank you :)

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He used Principal Component Analysis (PCA) to compress 1536-dimensional word embeddings into a 3D viz, tracking how the AI builds responses word by word.

The project shows two linked visualizations:
↳ A 3D cube showing bifurcating paths
↳ A tree diagram revealing word probabilities.

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Data scientist Santiago Ortiz mapped ChatGPT's thinking by running the prompt "𝘐𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 𝘪𝘴" hundreds of times with a high temperature setting of 1.6 for varied responses.

Link to the project: moebio.com/mind

Fascinating Visualization on How ChatGPT Builds Sentences in Real-Time 👇

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#datascience #python #machinelearning #MLSky

Hi, how do I join? Still figuring out how 🦋 works :)
Already hit the “Like” in the feed btw

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All course materials are executable: slides are Jupyter notebooks with generated figures. Readers can tweak parameters and regenerate them.

Course Website & Materials: kuleshov-group.github.io/aml-website/

Lecture Notes: kuleshov-group.github.io/aml-book/int...

FREE Course: Applied Machine Learning - Cornell CS 5787 👇

Starting from the basics, it covers key ML algorithms (linear regression, kernel methods, neural networks, etc.), their mathematical foundations, and how to apply them.

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#datascience #python #machinelearning

TopAIsJobs - The Newsletter | Gina Acosta | Substack Looking to grow in your Data, AI, or tech role? We have the resources you need. Get top AI jobs, deep dives, expert advice, research papers and more in your inbox every week! Click to read TopAIsJobs ...

👉 Get free resources, curated articles, and expert tips on Data and AI: topaisjobs.substack.com

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The researchers, collaborating with Facebook AI, initially set out to explore weaknesses in machine learning models. The outcome is a vibrant pattern on clothing that AI cameras fail to detect, essentially making the wearer invisible to machines.

This sweater acts as an invisibility cloak against AI 🤯

Developed by a team at the University of Maryland, it features "adversarial patterns" that confuse most common object detectors. This means AI systems can't spot the person wearing it.

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#data #ai #machinelearning

git commit -m 'update_final_v2' 😂

#programming #coding #developer

Here's what it covers:

✔ Day 1 - Foundational Models & Prompt Engineering
✔ Day 2 - Embeddings and Vector Stores/Databases
✔ Day 3 - Generative AI Agents
✔ Day 4 - Domain-Specific LLMs
✔ Day 5 - MLOps for Generative AI

Here's the link: www.kaggle.com/learn-guide/...

Google has released all the content from its '5-Day Gen AI Intensive Course' on Kaggle for FREE! 👇

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#data #machinelearning #google

TopAIsJobs - The Newsletter | Gina Acosta | Substack Looking to grow in your Data, AI, or tech role? We have the resources you need. Get top AI jobs, deep dives, expert advice, research papers and more in your inbox every week! Click to read TopAIsJobs ...

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9. Transformers United - www.youtube.com/watch?v=P127...

👉 Get free resources, curated articles, and expert tips on Data and AI: topaisjobs.substack.com

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5. Reinforcement Learning - www.youtube.com/watch?v=WsvF...

6. Deep Generative Models - www.youtube.com/watch?v=XZ0P...

7. Building Large Language Models (LLMs) - www.youtube.com/watch?v=9vM4...

8. Machine Learning with Graphs - www.youtube.com/watch?v=JAB_...

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1. Probability for Computer Scientists - www.youtube.com/watch?v=2MuD...

2. Machine Learning Full Course taught by Andrew Ng - www.youtube.com/watch?v=jGwO...

3. NLP with Deep Learning - www.youtube.com/watch?v=rmVR...

4. Machine Learning Explainability - www.youtube.com/watch?v=_DYQ...

All the FREE Stanford University Machine Learning Lectures 👇

Learn about Probability, NLP, LLMs, Transformers, and more ...

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#data #machinelearning #datascience #ai

TopAIsJobs - The Newsletter | Gina Acosta | Substack Looking to grow in your Data, AI, or tech role? We have the resources you need. Get top AI jobs, deep dives, expert advice, research papers and more in your inbox every week! Click to read TopAIsJobs ...

👉 Get free resources, curated articles, and expert tips on Data and AI: topaisjobs.substack.com

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• 𝐃𝐈𝐒𝐓𝐈𝐍𝐂𝐓: The DISTINCT keyword can be used to ensure that only distinct rows are returned in the result set.
• 𝐎𝐑𝐃𝐄𝐑 𝐁𝐘: The ORDER BY clause is used to sort the result set in ascending or descending order.
• 𝐋𝐈𝐌𝐈𝐓: The LIMIT clause can be used to restrict the number of rows returned.

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• 𝐆𝐑𝐎𝐔𝐏 𝐁𝐘: The GROUP BY clause is used to group the data based on one or more columns.
• 𝐇𝐀𝐕𝐈𝐍𝐆: The HAVING clause is used to filter the grouped data based on specific conditions.
• 𝐒𝐄𝐋𝐄𝐂𝐓: The SELECT clause specifies the columns that will be returned in the result set.

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Here’s a breakdown of the SQL execution order:

• 𝐅𝐑𝐎𝐌/𝐉𝐎𝐈𝐍: The FROM clause specifies the tables from which the data will be retrieved. The JOIN clause can be used to combine data from multiple tables.
• 𝐖𝐇𝐄𝐑𝐄: The WHERE clause is used to filter the data based on specific conditions.