Text-to-SQL with LLMs - Embracing the Future of Data Interaction
Explore the future of database interaction with our comprehensive guide on Text-to-SQL technology using Large Language Models (LLMs).
22 tutorials
Explore the future of database interaction with our comprehensive guide on Text-to-SQL technology using Large Language Models (LLMs).
This ChatGPT style guide presents voice and tone options and explains how you can trigger them with simple language.
Learn about the top 9 use cases for implementing OpenAI's GPT models such as ChatGPT, and Davinci in a business context.
In this step-by-step tutorial, we show how to generate detailed OpenAI DALL-E prompts using ChatGPT in Python.
Unleash the power of AI with OpenAI's models: A comprehensive guide on how to interact with ChatGPT, and other language models via the OpenAI API in Python.
In this tutorial, we will use Python and the scikit-learn library to apply hierarchical clustering to a dataset of customer data.
The Python library Pandas is a useful package that makes it easy to access a variety of popular data sources on the Internet.
Using confusion matrix and error metrics for measuring classification performance in machine learning with Python.
This tutorial presents k-mean clustering and how to perform a cluster analysis on synthetic data with Python and Scikit-Learn.
The Gate.io API provides access to market prices of a variety of cryptocurrencies. Learn to retrieve price data via the API using Python.
This article lays the foundation for building a Twitter bot by showing how to submit tweets via the Twitter API using Python and Tweepy.
Learn how to request crypto price data from the Coinmarketcap REST API and store it in a local SQLite DB using Python and Pewee.
Discover how you can use the twitter API to access tweets and images from twitter with Python and use them in your data science project.
Learn about image classification with deep learning and develop a convolutional neural network that distinguishes between cats and dogs!
This article deals with sentiment analysis and shows how to build a sentiment classifier using logistic regression and naive Bayes in Python.
Learn to use logistic regression to solve two-class prediction problems in Python by classifying online shoppers' purchase intentions.
This tutorial presents six regression error metrics to measure model performance and shows how to implement them with Python and Scikit-learn
COVID-19 has had a strong impact on the global stock market. We can measure this influence with a stock market correlation matrix in Python.
This article shows how to train a univariate neural network model for stock market forecasting with Python and Scikit-learn.
This article shows how to access remote data sources via REST APIs in Python. Two examples are given: Using Pandas Webreader and Requests.
Get started with Python Machine Learning and set up the Anaconda Python Environment and Python packages, incl. Jupyter Notebooks.
Want to learn about flight delay prediction? This tutorial develops a classifier in Azure Machine Learning that predicts flight delays.