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Generative AI Projects with PandasAI - BaDshaH - 05-14-2024
![[Image: ca121e6a0757060baaa5c80ac7801066.jpg]](https://i123.fastpic.org/big/2024/0514/66/ca121e6a0757060baaa5c80ac7801066.jpg)
Published 5/2024
Created by Tirendaz Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 7 Lectures ( 1h 27m ) | Size: 448 MB
Learn how to perform data science projects with Ollama, LangChain, Streamlit and modern APIs using Pandas AI
What you'll learn:
End-to-end genearative AI projects
How to use PandasAI?
How to analyze data with PandasAI?
How to visualize data with PandasAI?
How to work with PandasAI using Ollama?
How to work with databases with PandasAI?
How to build apps with PandasAI and Streamlit?
How to build chatbots with modern api tools?
Requirements:
Python
A computer with at least 8 GB RAM
Description:
Implementing data science projects is a challenge. When it comes to data manipulation and data analysis, as you know, pandas is king. Pandas AI is a game changer in data science that you can think of as a smart version of pandas.Pandas AI is nothing but a Python tool that allows you to explore, clean, and analyze your data using generative AI. That means that you can talk to your data using this tool. You can think of Pandas AI as a smart version of pandas.Let me explain PandasAI features. This tool allows you to ask questions to your data in natural language. Using this tool, you can analyze your data and generate graphs and charts by talking to your dataset. Plus, PandasAI helps you clean your data by addressing missing values. Thus, you can improve the quality of your data. With this library, you can connect to various data sources like CSV, XLSX, PostgreSQL, MySQL, BigQuery, Databrick, Snowflake, etc. and analyze data in these sources. In this course, we'll cover how to use PandasAI step-by-step. At the end of this course, you can see the power of the PandasAI for data science. To show this, we'll perform data science projects with modern libraries such as Ollama, Langchain, and Streamlit from scratch.See you in the course.
Who this course is for:
Data scientists
Machine learning engineers
AI engineers
Developers
Generative AI enthusiasts
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