Two comparisons of data analysts to Code Interpreter: "Experimental results show that GPT-4 can achieve comparable performance to humans" https://
arxiv.org/pdf/2305.15038
.pdf
… GPT-4 scores over 90% on exams, the data science field is “on the verge of a paradigm shift” https://
arxiv.org/pdf/2307.02792
v2.pdf
…
CODE
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GPT-4 Achieves Human-Level Performance in Data Analysis
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Time Complexity of 10 Machine Learning Algorithms Infographic
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Time complexity of 10 #MachineLearning algorithms in a single #infographic Source: https://
linkedin.com/feed/update/ur
n:li:activity:7177764655308623872?utm_source=share&utm_medium=member_ios
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50+ Data Analytics Projects with Code Implementation Guide
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50 + Implemented #DataAnalytics Projects with code — compiled by @NainaChaturved8 ————
#BigData #DataScience #Analytics #MachineLearning #AI #AnalyticThinking https://
medium.com/coders-mojo/da
ta-analytics-projects-series-b6abc25e4815
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Maestro AI generates complete paint app with single prompt
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Just added one of the most requested features to Maestro. 🪄
— Pietro Schirano (@skirano) 24 mars 2024
Now, when working on code projects, it actually creates each individual file as well.
Watch this wild demo, where Maestro makes a full-featured paint clone for me in around 3 minutes with a single prompt. 🔥 pic.twitter.com/E97XwK551yJust added one of the most requested features to Maestro. Now, when working on code projects, it actually creates each individual file as well. Watch this wild demo, where Maestro makes a full-featured paint clone for me in around 3 minutes with a single prompt.
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AI Trends Dashboard: Multi-Page Dash App with LangChain
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Trends in AI – Plotly Dash App with LLM A multi-page Python Dash app highlighting the growing role of AI in today's world. It incorporates a LangChain Pandas Agent to empower users with deeper insights into the datasets. YouTube: https://
youtube.com/watch?v=t3O-0m
zLJzI
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Python Feature Engineering Cookbook: 70+ Recipes for Machine Learning
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#Python #FeatureEngineering Cookbook with 70+ recipes for creating, engineering, & transforming features for #MachineLearning models (2nd Edition): http://
amzn.to/3Ssdh5X via @PacktPublishing ————
#AI #BigData #DataStrategy #DataLiteracy #DataScience #DataScientists #Coding #ML -
Real-Time Analytics Systems: Kafka and Pinot Integration Guide
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Building Real-Time #Analytics Systems — From Events to Insights with Apache Kafka and Apache Pinot: http://
amzn.to/403A8XQ
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#ad #AI #BigData #DataScience #Statistics #MachineLearning #DataScientists #PredictiveAnalytics #PrescriptiveAnalytics #AnalyticsStrategy #DataDriven -
Flowise APIs Tutorial: Custom LLM Orchestration Integration
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Our APIs allow developers to connect 3rd party integrations with custom LLM orchestration.
— FlowiseAI (@FlowiseAI) 24 mars 2024
In this video, @leonvz covers a full tutorial on how to use Flowise APIs in details.
Now you know how to spend your Sunday😉https://t.co/iB9thwt6mR https://t.co/RDEOTnGK5L pic.twitter.com/pza4ouXZqhOur APIs allow developers to connect 3rd party integrations with custom LLM orchestration. In this video, @leonvz covers a full tutorial on how to use Flowise APIs in details. Now you know how to spend your Sunday https://
youtu.be/9R5zo3IVkqU?si
=Jnaua4macSiX0ohP
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LangGraph Agent Supervisor with Anthropic Models Open-Sourced
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Agent Supervisor with Anthropic We've put a lot of work into LangGraph to make it the best run time for agents. Most of the examples are with OpenAI, but @eucheetan just open-sourced an example with @AnthropicAI models https://
github.com/prof-frink-lab
/slangchain/blob/main/docs/modules/graphs/examples/anthropic/agent_supervisor.ipynb
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Retrieval-Augmented Fine-Tuning: Combining RAG and Fine-tuning
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10/ Retrieval-Augmented Fine-Tuning Combines the benefits of RAG and fine-tuning to improve a model's ability to answer questions in "open-book" in-domain settings; combining it with RAFT's CoT-style response helps to improve reasoning.