AI Tutorials

In this tutorial, you'll learn how to work with the OpenAI Python package to programmatically have conversations with ChatGPT.

LangChain is a framework for including AI from large language models inside data pipelines and applications. This tutorial provides an overview of what you can do with LangChain, including the problems that LangChain solves and examples of data use cases.

Discover the powerful capabilities of OpenAI Whisper Python API for transcription and translation. It comes with multi-language support and prompt enhancement for accurate transcription.

Learn how to use ChatGPT in a real-life end-to-end data science project. We will use it for project planning, data analysis, data preprocessing, model selection, hyperparameter tuning, developing a web app, and deploying it on the Spaces.

Discover what text classification is, how it works, and successful use cases. Explore end-to-end examples of how to build a text preprocessing pipeline followed by a text classification model in Python.

Learn what natural language processing (NLP) is and discover its real-world application, using Google BERT to process text datasets.

Learn how gradient descent works and how to implement it.

Learn about the most popular deep learning model RNN and get hands-on experience by building a MasterCard stock price predictor.

The tutorial answers the most frequently asked questions about deep learning and explores various aspects of deep learning with real-life examples.

We help simplify sentiment analysis using Python in this tutorial. You will learn how to build your own sentiment analysis classifier using Python and understand the basics of NLP (natural language processing).

Discover Long Short-Term Memory (LSTM) networks in Python and how you can use them to make stock market predictions!

Python NLTK (natural language toolkit) sentiment analysis tutorial. Learn how to create and develop sentiment analysis using Python. Follow specific steps to mine and analyze text for natural language processing.