Building a Conversational Voice Bot with Azure OpenAI and Python: The Future of Human and Machine Interaction
Learn how to build a conversational voice bot in Python with the latest models from Azure OpenAI and Azure AI Speech Services.
36 tutorials
Learn how to build a conversational voice bot in Python with the latest models from Azure OpenAI and Azure AI Speech Services.
In this step-by-step tutorial, we show how to generate detailed OpenAI DALL-E prompts using ChatGPT in Python.
Build a leakage-safe, reproducible machine-failure classifier and evaluate rare-event performance with appropriate baselines and metrics.
In this tutorial, we will use Python and the scikit-learn library to apply hierarchical clustering to a dataset of customer data.
This tutorial gives an overview of Facebook Prophet and shows how to use the framework in Python to create a univariate time series forecast.
This article combines blockchain data and historic crypto prices from CryptoCompare in a comprehensive on-chain analysis using Python.
The Python library Pandas is a useful package that makes it easy to access a variety of popular data sources on the Internet.
This guide provides tips on feature exploration, engineering, and selection for machine learning using Python and Scikit-Learn
This article shows how to employ a bag of words model and cosine similarities to create a content-based movie recommender with Python.
Cluster cryptocurrency returns with affinity propagation, estimate a sparse dependency network, and visualize the 2023-2025 market structure in Python.
Learn how to use Random Search to tune the model hyperparameters of a Random Forest with Python that predicts house sale prices.
This tutorial teaches the basics of Big Data analytics with Pyspark, based on the ingestion, processing, and analysis of Zurich weather data.
This tutorial develops and evaluates a Keras multi-output regression model that forecasts ten future Apple trading sessions in one pass.
This tutorial presents k-mean clustering and how to perform a cluster analysis on synthetic data with Python and Scikit-Learn.
This article describes multivariate anomaly detection in the example of credit card fraud using Random Isolation Forests in Python
In this article, we will create a Twitter signal bot in Python that analyzes crypto prices for notable events and notifies users on Twitter.
The Gate.io API provides access to market prices of a variety of cryptocurrencies. Learn to retrieve price data via the API using Python.
Build and evaluate a reproducible multiclass model for historical San Francisco incident categories, including responsible-use limitations.
This Python tutorial shows how to use Auto-ARIMA for time series forecasting using the example of forecasting beer sales.
Create color-coded cryptocurrency price charts with Python to visualize the lag between price points and the bitcoin halving.
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 tutorial shows how to build a customer churn prediction model in telecommunications. We will use Python and measure feature importance.
Learn how to tune the model hyperparameters of a Random Forest that predicts the survival of Titanic passengers using grid search in Python.
Test causal technical indicators in a leakage-free NASDAQ forecasting experiment with Python, Keras, and chronological evaluation.
A compact, reproducible sentiment-analysis example using synthetic text data, TF-IDF features, and a comparison of Naive Bayes and Logistic Regression.
This tutorial builds and evaluates a Keras multivariate LSTM that forecasts the next-session NASDAQ Composite return.
Learn to use logistic regression to solve two-class prediction problems in Python by classifying online shoppers' purchase intentions.
Learn six regression error metrics, their limitations, and how to evaluate a time series model against a baseline with Python and scikit-learn.
This tutorial shows how to create and evaluate a recursive multi-step forecast for a rising sine curve using Keras LSTM layers in Python.
Build reproducible world and regional choropleth maps with GeoPandas, Natural Earth boundaries, and an archived COVID-19 dataset.
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 tutorial shows how to build a direct five-trading-session forecast using a Keras recurrent neural network and 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.