Stanford University has released these cheatsheets on Machine Learning, Deep Learning, Statistics, and Linear Algebra. Use this as your reference next time working with them:
@sumanth_077
-
AI-Powered Writing Integration Interest
By
–
The integration of AI to power writing is something that I really liked will definitely check this out.
-

Free Deep Learning Book: FastAI and PyTorch Fundamentals
By
–
Here is the free version of the book Deep Learning for Coders with fastai and PyTorch that helps you with. → Deep Learning basics and Implementing the algorithms from scratch
→ Training models in computer vision, NLP and much more. Save this! http://
github.com/fastai/fastbook -
Daily Python, Machine Learning and Language Models Tutorials
By
–
Every day, I share tutorials and simplify complex topics around Python, Machine Learning & Language Models. Follow me → @Sumanth_077 to ensure you don't miss that. Like/RT the first tweet to support my work and help this reach more people.
-
Steamship Simplifies AI App Development and Deployment
By
–
Thanks for Sharing Rohit. @GetSteamship makes it really easy to develop and deploy AI Apps.
-
Daily Python Machine Learning and Language Models Tutorials
By
–
Every day, I share tutorials and simplify complex topics around Python, Machine Learning & Language Models. Follow me → @Sumanth_077 to ensure you don't miss that. Like/RT the first tweet to support my work and help this reach more people.
-
Building Chatbot Applications with LangChain AI Framework
By
–
Chatbot is one such example of Lang Chain AI and the applications are endless. For a detailed explanation and to build more such applications with Langchain, check out the source code and docs Source Code – http://
github.com/steamship-core
/steamship-langchain/tree/main/examples/chatbot
… Docs: https://
steamship.com/build/langchai
n-apps
… -

Flask endpoints for chatbot customization and message handling
By
–
Add Flask-style endpoints and customize the bot by defining the chain. Below you can see two endpoints 1. To generate a Response for a Text – "send_message" 2. To give the full chat history – "transcript" Similarly add endpoints for your usecases. Server-side code:
-

Steamship Hosting with LangChain Integration for Chatbots
By
–
Steamship to host the APP the best part is it comes with an integration to langchain that makes it super easy to build and host the chatbot directly. To make it simple and easy to understand, Let's break the code into two Python scripts: Let's look at how we can implement it
-
Building a ChatGPT-like Chatbot with Langchain and Steamship
By
–
The goal is to build a simple chatbot like ChatGPT which can answer to specific questions Tech stack required 1. Langchain AI: Python package that provides a lots of integrations with tools like Open AI, HF and also end-to-end chains for diff applications 2. Steamship
