Build AI Agents using LangChain - Simple Python Implementation
811 بار بازدید -
7 ماه پیش
-
LLMs suffer from 2 major
LLMs suffer from 2 major drawbacks
* Even though the LLMs (Large Language Models) are trained on huge corpus of data, their knowledge is limited to the training data
* Outdated information
In order to solve the above two problems, LangChain Agents allow thinking and interacting with the world to solve tasks
In this video, we shall learn about LangChain Agents and build an agent using tools in LangChain in a step-by-step manner
References:
* Integrated tools in LangChain: https://python.langchain.com/docs/int...
* Types of Agents: https://js.langchain.com/docs/modules...
* Introduction to LangChain: Introduction to LangChain with Python...
* Building Chatbot using LangChain: Building a Chatgpt like Chatbot using...
If you find the content useful, make sure to give it a THUMBS UP :)
--------------------------------------------------------------------------------------------------------------------------------------
Why learn from datahat??
"Datahat is a bridge"
learners --- professionals by simplified data science
It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis
* Here are few interesting reads on our blog: Medium: souravagarwal54321
* Connect with us on linkedIn: LinkedIn: datahat-unfoldingmystery
* Book a mentorship session: https://topmate.io/datahat
--------------------------------------------------------------------------------------------------------------------------------------
Additionally, here are few more useful resources for beginners and curious data enthusiasts
1. kaggle: a platform to learn, practice, compete and win cash prizes [https://www.kaggle.com/]
2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [https://paperswithcode.com/]
3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [https://colab.research.google.com/]
Remember, "the greatest investment ever made is investment in self growth and learning"
* Even though the LLMs (Large Language Models) are trained on huge corpus of data, their knowledge is limited to the training data
* Outdated information
In order to solve the above two problems, LangChain Agents allow thinking and interacting with the world to solve tasks
In this video, we shall learn about LangChain Agents and build an agent using tools in LangChain in a step-by-step manner
References:
* Integrated tools in LangChain: https://python.langchain.com/docs/int...
* Types of Agents: https://js.langchain.com/docs/modules...
* Introduction to LangChain: Introduction to LangChain with Python...
* Building Chatbot using LangChain: Building a Chatgpt like Chatbot using...
If you find the content useful, make sure to give it a THUMBS UP :)
--------------------------------------------------------------------------------------------------------------------------------------
Why learn from datahat??
"Datahat is a bridge"
learners --- professionals by simplified data science
It provides a platform to learn, create and collaborate helping in the #career #transition to data science, machine learning and data analysis
* Here are few interesting reads on our blog: Medium: souravagarwal54321
* Connect with us on linkedIn: LinkedIn: datahat-unfoldingmystery
* Book a mentorship session: https://topmate.io/datahat
--------------------------------------------------------------------------------------------------------------------------------------
Additionally, here are few more useful resources for beginners and curious data enthusiasts
1. kaggle: a platform to learn, practice, compete and win cash prizes [https://www.kaggle.com/]
2. paperswithcode: website presenting the latest in machine learning and data science research and the code implementations [https://paperswithcode.com/]
3. google colab: a platform to run code, build machine learning solutions, explore the capabilities of GPU and TPU without any hassle in setting up the environment: [https://colab.research.google.com/]
Remember, "the greatest investment ever made is investment in self growth and learning"
7 ماه پیش
در تاریخ 1402/09/04 منتشر شده
است.
811
بـار بازدید شده