Data Analytics with Generative AI: A Detailed Guide

Welcome to Data Science Dojo's weekly newsletter, "The Data-Driven Dispatch".

For those who have spent countless hours toiling over code, the natural language replacement of coding is like a long-lost dream come true.

This breakthrough is good news for data analysts, who can now query CSV files, clean data, run models, and create visualizations, all with natural language.

Excited to learn how to leverage generative AI for data analytics? Let's dig in!

Here is some major progress happening in the AI landscape since we last met:

1) Microsoft Researchers Introduce "AutoGen": Microsoft researchers have introduced a preview of "Autogen". It is an innovative framework that simplifies the orchestration, optimization, and automation of Large Language Model workflows, enabling complex multi-agent conversations with capabilities ranging from automated tasks to human interactions. Learn more

2) OpenAI Releases Dall-E 3 - An Art Generator Powered by ChatGPT: OpenAI has announced Dall-E 3, an AI art tool that uses ChatGPT to simplify prompt engineering and enable more detailed and coherent AI-generated art. It allows users to interact conversationally with ChatGPT to create sophisticated artwork, lowering the complexity of generating AI art. Learn more

3) Google DeepMind's Tool "AlphaMissense" Can Pinpoint Causes of Genetic Diseases: AlphaMissense, a new AI tool by DeepMind, classifies the effects of 71 million 'missense' mutations, aiding in understanding genetic causes of diseases and accelerating research. Learn more

Leveraging LangChain Agents for Data Analytics

What are LangChain Agents?

LangChain acts as a crucial link between humans and Large Language Models. Within the LangChain framework, there exist multiple specialized agents, each dedicated to distinct domains. These agents play a pivotal role in simplifying user queries by breaking them down into a sequence of tasks that can be understood by LLMs. Read more

How LangChain Agents Enable Data Analytics with Natural Language:

Suppose you wish to execute a particular SQL query. In this scenario, the LangChain agent takes your natural language input, transforms it into an SQL query, retrieves the result, refines the model's understanding in case of errors, and finally delivers the response in natural language.

There are different LangChain Agents that you can use for different data analytics tasks. The most important LangChain agents include CSV , Pandas DataFrame , and SQL Database .

Here are some interesting reads on how you can leverage these agents for data analytics:

• How to Automate Data Analysis with LangChain Using Pandas Dataframe
• Create Your Own Data Analyst Assistant with Langchain Agents
• Query Database Using Natural Language — LangChain SQL Agents

Want to learn more about AI??Our?blog ?is the go-to source for the latest tech news.

Leveraging ChatGPT Plugins for Data Analytics:

Explore the top 6 ChatGPT plugins tailored for data science. These plugins encompass a wide array of functions, spanning tasks such as web browsing, automation, code interpretation, and streamlining workflow processes.

Learn more about these Plugins and what they specialize in here: 6 Best ChatGPT Plugins for Data Science .

Did this riddle trick you as a kid? Don't feel bad, even ChatGPT fell for it.

Data Visualization is one of the crucial aspects of data analytics which allows you to have a clear picture in mind of what's happening and what strategy to go with.

Get on this anticipated talk by Andrew C. Madson as he gives a comprehensive tutorial on how you can use generative AI for creating powerful visualizations allowing you to deliver great stories and drive impactful decision-making.

For a deeper dive into generative AI, visit our YouTube channel for tutorials and insights.

What is the Fine-tuning of Large Language Models?

Think of fine-tuning LLMs like teaching a dog a new trick without making it forget what it already knows.

Pre-trained models like GPT 4, and PaLM 2 are trained on massive data which enables them to have knowledge on a wide array of topics. However, for these LLMs to have mastery over specific topics like medicine, astronomy, etc. we fine-tune them with additional data in a specific domain. Learn more

Crash Course on Fine-tuning ChatGPT 3.5 Turbo:

Eager to become a pro at fine-tuning LLMs? Don't miss out on the live crash course led by Syed Hyder Ali Zaidi , a Data Scientist at Data Science Dojo, scheduled for October 10th.

Don't miss out on this opportunity and save a spot right away!

Intensive bootcamp to Become an Expert in Large Language Models

We understand that Generative AI might be a bit tricky to grasp because it has many different areas, like vector databases and orchestration frameworks, scattered around.

How do we solve this problem? We suggest you check out Data Science Dojo's comprehensive Large Language Models Bootcamp , where you not only gain an in-depth understanding of all essential topics but also delve into real-life case studies from big companies.

If you want to learn more about the curriculum and instructors, visit our website .

??We trust that you had a delightful and enriching experience with us this week, leaving you more knowledgeable than before! ??

?If you wish to use Python effectively for data analysis, check out our Python for Data Science Bootcamp .

? Don't forget to join?Data Science Dojo's Community ?and stay tuned to our ongoing events all the time.

Until we meet again, take care!