<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"><channel><title>relataly.com</title><description>Hands-on Python tutorials on machine learning, data science, and generative AI — with real-world business use cases in finance, retail, healthcare, and more.</description><link>https://www.relataly.com/</link><item><title>What is AI actually being used for?</title><link>https://www.relataly.com/ai-use-case-hub-real-world-ai-use-cases/14445/</link><guid isPermaLink="true">https://www.relataly.com/ai-use-case-hub-real-world-ai-use-cases/14445/</guid><description>Explore 3,000+ real-world AI use cases, save favorites, set company and industry alerts, and build your own impact-effort matrix for free.</description><pubDate>Sun, 14 Jun 2026 10:09:48 GMT</pubDate><category>Use Cases</category></item><item><title>Agentic Web Scraping with Azure AI Foundry Agent Service: Insights from Building AIUseCaseHub.com</title><link>https://www.relataly.com/agentic-web-scraping-with-azure-ai-foundry-agent-service-insights-from-building-aiusecasehub-com/14376/</link><guid isPermaLink="true">https://www.relataly.com/agentic-web-scraping-with-azure-ai-foundry-agent-service-insights-from-building-aiusecasehub-com/14376/</guid><description>Discover how AIUseCaseHub.com uses agentic web scraping with Azure AI Foundry Agent Service, multi-agent orchestration and tool calling.</description><pubDate>Sun, 15 Jun 2025 19:59:33 GMT</pubDate><category>Generative AI</category><category>Language Generation</category><category>Marketing Automation</category><category>Natural Language Processing</category><category>OpenAI</category><category>Prompt Engineering</category><category>Use Cases</category><category>Vector Databases</category></item><item><title>Six Shortcomings of Current LLMs I Expect From AGI</title><link>https://www.relataly.com/the-road-towards-general-artificial-intelligence-agi-a-few-thoughts-on-current-ai-limitations/14322/</link><guid isPermaLink="true">https://www.relataly.com/the-road-towards-general-artificial-intelligence-agi-a-few-thoughts-on-current-ai-limitations/14322/</guid><description>This article explores the limitations of current LLMs and highlights six key areas where AGI is expected to excel beyond today&apos;s AI models.</description><pubDate>Sat, 17 Feb 2024 12:59:39 GMT</pubDate><category>Generative AI</category><category>OpenAI</category></item><item><title>Building a Conversational Voice Bot with Azure OpenAI and Python: The Future of Human and Machine Interaction</title><link>https://www.relataly.com/voice-conversations-with-azure-ai/14291/</link><guid isPermaLink="true">https://www.relataly.com/voice-conversations-with-azure-ai/14291/</guid><description>Learn how to build a conversational voice bot in Python with the latest models from Azure OpenAI and Azure AI Spech Services.</description><pubDate>Thu, 08 Feb 2024 21:09:50 GMT</pubDate><category>Azure Machine Learning</category><category>ChatBots</category><category>Generative AI</category><category>OpenAI</category><category>Python</category></item><item><title>Text-to-SQL with LLMs - Embracing the Future of Data Interaction</title><link>https://www.relataly.com/text-to-sql-with-llms-embracing-the-future-of-data-interaction/14234/</link><guid isPermaLink="true">https://www.relataly.com/text-to-sql-with-llms-embracing-the-future-of-data-interaction/14234/</guid><description>Explore the future of database interaction with our comprehensive guide on Text-to-SQL technology using Large Language Models (LLMs).</description><pubDate>Thu, 28 Dec 2023 11:07:58 GMT</pubDate><category>Finance</category><category>Healthcare</category><category>Insurance</category><category>Logistics</category><category>Natural Language Processing</category><category>Text-to-sql</category></item><item><title>Building a Virtual AI Assistant (aka Copilot) for Your Software Application: Harnessing the Power of LLMs like ChatGPT</title><link>https://www.relataly.com/building-a-digital-ai-assistant-for-your-software-application/14056/</link><guid isPermaLink="true">https://www.relataly.com/building-a-digital-ai-assistant-for-your-software-application/14056/</guid><description>Explore the new era of digital interaction with LLM-powered virtual AI assistants. 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Customize the characters; code on GitHub.</description><pubDate>Mon, 24 Apr 2023 22:44:52 GMT</pubDate><category>ChatBots</category><category>Generative AI</category><category>Language Generation</category><category>OpenAI</category></item><item><title>How Far are Swiss Enterprises in Adopting OpenAI&apos;s GPT Models?</title><link>https://www.relataly.com/exploring-the-journey-of-the-swiss-economy-in-adopting-openai-chatgpt-and-co/13486/</link><guid isPermaLink="true">https://www.relataly.com/exploring-the-journey-of-the-swiss-economy-in-adopting-openai-chatgpt-and-co/13486/</guid><description>How the Swiss economy is adopting OpenAI — from companies yet to explore its potential to those with a proven track record of implementing it.</description><pubDate>Sun, 23 Apr 2023 21:03:03 GMT</pubDate><category>Finance</category><category>Generative AI</category><category>Healthcare</category><category>Insurance</category><category>Logistics</category><category>Manufacturing</category><category>Natural Language Processing</category><category>Telecommunications</category></item><item><title>ChatGPT Prompt Engineering Guide: Practical Advice for Business Use Cases</title><link>https://www.relataly.com/mastering-prompt-engineering-for-chatgpt-a-practical-guide-for-businesses/13134/</link><guid isPermaLink="true">https://www.relataly.com/mastering-prompt-engineering-for-chatgpt-a-practical-guide-for-businesses/13134/</guid><description>Discover typical challenges and learn how to engineer prompts for the successful use of ChatGPT in a business context.</description><pubDate>Thu, 30 Mar 2023 22:25:44 GMT</pubDate><category>Finance</category><category>Generative AI</category><category>Healthcare</category><category>Insurance</category><category>Logistics</category><category>Machine Learning</category><category>Natural Language Processing</category><category>OpenAI</category><category>Prompt Engineering</category></item><item><title>Using LLMs (OpenAI&apos;s ChatGPT) to Streamline Digital Experiences</title><link>https://www.relataly.com/eliminating-friction-how-openais-gpt-streamlines-online-experiences-and-reduces-the-need-for-google-searches/13171/</link><guid isPermaLink="true">https://www.relataly.com/eliminating-friction-how-openais-gpt-streamlines-online-experiences-and-reduces-the-need-for-google-searches/13171/</guid><description>Learn about digital friction and how OpenAI&apos;s GPT technology can help reduce it, improving user experience across products and services.</description><pubDate>Mon, 27 Mar 2023 08:35:21 GMT</pubDate><category>Finance</category><category>Healthcare</category><category>Insurance</category><category>Logistics</category><category>Marketing Automation</category><category>Natural Language Processing</category><category>OpenAI</category><category>Retail</category><category>Use Cases</category></item><item><title>ChatGPT Style Guide: Understanding Voice and Tone Prompt Options for Engaging Conversations</title><link>https://www.relataly.com/chatgpt-style-guide-understanding-voice-and-tone-options-for-engaging-conversations/13065/</link><guid isPermaLink="true">https://www.relataly.com/chatgpt-style-guide-understanding-voice-and-tone-options-for-engaging-conversations/13065/</guid><description>This ChatGPT style guide presents voice and tone options and explains how you can trigger them with simple language.</description><pubDate>Sun, 19 Mar 2023 19:42:03 GMT</pubDate><category>Algorithms</category><category>Feature Engineering</category><category>Language Generation</category><category>OpenAI</category><category>Prompt Engineering</category></item><item><title>Using Fairlearn to Build Fair Machine Machine Learning Models with Python: Step-by-Step Towards More Responsible AI</title><link>https://www.relataly.com/building-fair-machine-machine-learning-models-with-fairlearn/12804/</link><guid isPermaLink="true">https://www.relataly.com/building-fair-machine-machine-learning-models-with-fairlearn/12804/</guid><description>Move towards responsible AI by using FairLearn, an open-source Python package for assessing and mitigating unfairness in machine learning.</description><pubDate>Thu, 09 Mar 2023 23:45:16 GMT</pubDate><category>Data Science</category><category>Decision Trees</category><category>Fairlearn</category><category>Hyperparameter Tuning</category><category>Responsible AI</category></item><item><title>What is the Business Value of ChatGPT and other Large Generative Language Models?</title><link>https://www.relataly.com/openai-gpt-chatgpt-in-a-business-context-whats-the-value-proposition/12282/</link><guid isPermaLink="true">https://www.relataly.com/openai-gpt-chatgpt-in-a-business-context-whats-the-value-proposition/12282/</guid><description>Discover the unique value proposition of OpenAI&apos;s GPT models, including ChatGPT, and why they&apos;re causing such a buzz in the world of AI.</description><pubDate>Sat, 25 Feb 2023 17:30:59 GMT</pubDate><category>Finance</category><category>Healthcare</category><category>Insurance</category><category>Language Generation</category><category>Logistics</category><category>Manufacturing</category><category>OpenAI</category><category>Sentiment Analysis</category><category>Topic Modelling</category><category>Use Cases</category></item><item><title>9 Business Use Cases of OpenAI&apos;s ChatGPT</title><link>https://www.relataly.com/business-use-cases-for-openai-gpt-models-chatgpt-davinci/12200/</link><guid isPermaLink="true">https://www.relataly.com/business-use-cases-for-openai-gpt-models-chatgpt-davinci/12200/</guid><description>Learn about the top 9 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landscape. 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Python</title><link>https://www.relataly.com/predictive-maintenance-predicting-machine-failure-with-python/10618/</link><guid isPermaLink="true">https://www.relataly.com/predictive-maintenance-predicting-machine-failure-with-python/10618/</guid><description>By using machine learning and Python, businesses can predict equipment failures before they happen and optimize their maintenance cycles.</description><pubDate>Sun, 08 Jan 2023 20:34:44 GMT</pubDate><category>Algorithms</category><category>Classification (multi-class)</category><category>Cross-Validation</category><category>Data Visualization</category><category>Exploratory Data Analysis (EDA)</category><category>Gradient Boosting</category><category>Machine Learning</category><category>Manufacturing</category><category>Plotly</category><category>Predictive Maintenance</category><category>Python</category><category>Scikit-Learn</category><category>Seaborn</category><category>Yahoo Finance API</category></item><item><title>How to Use Hierarchical Clustering For Customer Segmentation in Python</title><link>https://www.relataly.com/customer-segmentation-using-hierarchical-clustering-in-python/11335/</link><guid isPermaLink="true">https://www.relataly.com/customer-segmentation-using-hierarchical-clustering-in-python/11335/</guid><description>In this tutorial, we will use Python and the scikit-learn library to apply hierarchical clustering to a dataset of customer data.</description><pubDate>Thu, 22 Dec 2022 18:50:14 GMT</pubDate><category>Agglomerative Clustering</category><category>Algorithms</category><category>Clustering</category><category>Customer Segmentation</category><category>Data Science</category><category>Data Visualization</category><category>Exploratory Data Analysis (EDA)</category><category>Finance</category><category>Insurance</category><category>Kaggle Competitions</category><category>Machine Learning</category><category>Marketing Automation</category><category>Python</category><category>Scikit-Learn</category><category>Seaborn</category><category>Telecommunications</category><category>Use Cases</category></item><item><title>Univariate Stock Market Forecasting using Facebook Prophet in Python</title><link>https://www.relataly.com/time-series-forecasting-using-facebook-prophet-in-python/10351/</link><guid isPermaLink="true">https://www.relataly.com/time-series-forecasting-using-facebook-prophet-in-python/10351/</guid><description>This tutorial gives an overview of Facebook Prophet and shows how to use the framework in Python to create a univariate time series forecast.</description><pubDate>Thu, 15 Dec 2022 22:54:34 GMT</pubDate><category>CryptoCompare API</category><category>Facebook Prophet</category><category>Finance</category><category>Python</category><category>REST APIs</category><category>Seaborn</category><category>Stock Market Forecasting</category><category>Time Series Forecasting</category><category>Use Cases</category><category>Yahoo Finance API</category></item><item><title>Unlocking the Potential of Machine Learning in the Insurance Industry: Five Use Cases with High Business Value</title><link>https://www.relataly.com/top-5-machine-learning-use-cases-in-insurance/10489/</link><guid isPermaLink="true">https://www.relataly.com/top-5-machine-learning-use-cases-in-insurance/10489/</guid><description>Machine learning is transforming the insurance industry by providing new and powerful ways to analyze and manage risk.</description><pubDate>Sat, 10 Dec 2022 17:18:32 GMT</pubDate><category>Insurance</category><category>Use Cases</category></item><item><title>On-Chain Analytics: Metrics for Analyzing Blockchains in Python</title><link>https://www.relataly.com/seven-metrics-for-on-chain-analysis-in-python/10098/</link><guid isPermaLink="true">https://www.relataly.com/seven-metrics-for-on-chain-analysis-in-python/10098/</guid><description>This article combines blockchain data and historic crypto prices from CryptoCompare in a comprehensive on-chain analysis using Python.</description><pubDate>Sat, 12 Nov 2022 12:05:00 GMT</pubDate><category>Blockchain &amp; Crypto Analytics</category><category>Correlation</category><category>Crypto Exchange APIs</category><category>CryptoCompare API</category><category>Data Science</category><category>Finance</category><category>Python</category><category>REST APIs</category><category>Seaborn</category><category>Use Cases</category></item><item><title>Using Pandas DataReader to Access Online Data Sources in Python</title><link>https://www.relataly.com/using-pandas-datareader-in-python/10934/</link><guid isPermaLink="true">https://www.relataly.com/using-pandas-datareader-in-python/10934/</guid><description>The Python library Pandas is a useful package that makes it easy to access a variety of popular data sources on the Internet.</description><pubDate>Sat, 15 Oct 2022 18:14:00 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Regression</category><category>Machine Learning</category><category>Measuring Model Performance</category><category>Python</category><category>Random Decision Forests</category><category>Sales Forecasting</category><category>Scikit-Learn</category><category>Seaborn</category><category>Simple Regression</category><category>Use Cases</category></item><item><title>Create a Personalized Movie Recommendation Engine using Content-based Filtering in Python</title><link>https://www.relataly.com/content-based-movie-recommender-using-python/4294/</link><guid isPermaLink="true">https://www.relataly.com/content-based-movie-recommender-using-python/4294/</guid><description>This article shows how to employ a bag of words model and cosine similarities to create a content-based movie recommender with Python.</description><pubDate>Mon, 25 Jul 2022 11:29:00 GMT</pubDate><category>Content-based Filtering</category><category>Correlation</category><category>Cosine Similarity</category><category>Machine Learning</category><category>nltk</category><category>Python</category><category>Recommender Systems</category><category>Retail</category><category>Scikit-Learn</category><category>Seaborn</category></item><item><title>Unveiling Hidden Patterns in the Cryptocurrency Market with Affinity Propagation and Python</title><link>https://www.relataly.com/crypto-market-cluster-analysis-using-affinity-propagation-python/8114/</link><guid isPermaLink="true">https://www.relataly.com/crypto-market-cluster-analysis-using-affinity-propagation-python/8114/</guid><description>This tutorial shows how to use affinity propagation to analyze asset clusters in the crypto market using Python.</description><pubDate>Mon, 02 May 2022 18:34:02 GMT</pubDate><category>Affinity Propagation (Clustering)</category><category>Clustering</category><category>Coinmarketcap API</category><category>Correlation</category><category>Covariance</category><category>Crypto Exchange APIs</category><category>Data Visualization</category><category>Dimensionality Reduction</category><category>Finance</category><category>Python</category><category>Scikit-Learn</category><category>Seaborn</category><category>Stock Market Forecasting</category><category>Time Series Forecasting</category></item><item><title>Using Random Search to Tune the Hyperparameters of a Random Decision Forest with Python</title><link>https://www.relataly.com/using-random-search-to-tune-the-hyperparameters-of-a-random-decision-forest-with-python/6875/</link><guid isPermaLink="true">https://www.relataly.com/using-random-search-to-tune-the-hyperparameters-of-a-random-decision-forest-with-python/6875/</guid><description>Learn how to use Random Search to tune the model hyperparameters of a Random Forest with Python that predicts house sale prices.</description><pubDate>Thu, 07 Apr 2022 15:55:36 GMT</pubDate><category>Algorithms</category><category>Classification 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Visualization</category><category>PySpark</category><category>Python</category><category>Seaborn</category><category>Weather Analytics</category></item><item><title>Getting Started with Big Data Analytics - Apache Spark Concepts and Architecture</title><link>https://www.relataly.com/introduction-to-bigdata-analytics-with-apache-spark-concepts-and-architecture/6324/</link><guid isPermaLink="true">https://www.relataly.com/introduction-to-bigdata-analytics-with-apache-spark-concepts-and-architecture/6324/</guid><description>This tutorial explains the concepts and architecture behind Apache Spark, a mighty big data processing and analytics framework.</description><pubDate>Tue, 22 Mar 2022 21:56:52 GMT</pubDate><category>PySpark</category></item><item><title>How to Measure the Performance of a Machine Learning Classifier with Python and Scikit-Learn?</title><link>https://www.relataly.com/measuring-classification-performance-in-machine-learning-with-python-and-scikit-learn/846/</link><guid isPermaLink="true">https://www.relataly.com/measuring-classification-performance-in-machine-learning-with-python-and-scikit-learn/846/</guid><description>Using confusion matrix and error metrics for measuring classification performance in machine learning with Python.</description><pubDate>Fri, 31 Dec 2021 17:37:00 GMT</pubDate><category>Classification (multi-class)</category><category>Classification (two-class)</category><category>Healthcare</category><category>Machine Learning</category><category>Measuring Model Performance</category><category>Random Decision Forests</category></item><item><title>Stock Market Forecasting Neural Networks for Multi-Output Regression in Python</title><link>https://www.relataly.com/stock-price-prediction-multi-output-regression-using-neural-networks-in-python/5800/</link><guid isPermaLink="true">https://www.relataly.com/stock-price-prediction-multi-output-regression-using-neural-networks-in-python/5800/</guid><description>This tutorial develops a 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GMT</pubDate><category>Algorithms</category><category>Clustering</category><category>Correlation</category><category>Covariance</category><category>K-Means</category><category>Python</category><category>Scikit-Learn</category><category>Seaborn</category><category>Synthetic Data</category><category>Use Cases</category></item><item><title>Multivariate Anomaly Detection on Time-Series Data in Python: Using Isolation Forests to Detect Credit Card Fraud</title><link>https://www.relataly.com/multivariate-outlier-detection-using-isolation-forests-in-python-detecting-credit-card-fraud/4233/</link><guid isPermaLink="true">https://www.relataly.com/multivariate-outlier-detection-using-isolation-forests-in-python-detecting-credit-card-fraud/4233/</guid><description>This article describes multivariate anomaly detection in the example of credit card fraud using Random Isolation Forests in Python</description><pubDate>Wed, 16 Jun 2021 07:33:00 GMT</pubDate><category>Anomaly Detection</category><category>Classification (two-class)</category><category>Finance</category><category>Fraud Detection</category><category>K-Nearest Neighbors (KNN)</category><category>Local Outlier Factor</category><category>Python</category><category>Random Isolation Forest</category><category>Scikit-Learn</category><category>Seaborn</category></item><item><title>Build a High-Performing Movie Recommender System using Collaborative Filtering in Python</title><link>https://www.relataly.com/building-a-movie-recommender-using-collaborative-filtering/4376/</link><guid isPermaLink="true">https://www.relataly.com/building-a-movie-recommender-using-collaborative-filtering/4376/</guid><description>This article shows how to build a recommender system for movies with python. The approach used is based on collaborative filtering.</description><pubDate>Mon, 31 May 2021 10:29:35 GMT</pubDate><category>Algorithms</category><category>Collaborative Filtering</category><category>Recommender Systems</category><category>Recommender Systems</category><category>Retail</category><category>Surprise Lib</category><category>Use Cases</category></item><item><title>Automate Crypto Trading with a Python-Powered Twitter Bot and Gate.io Signals</title><link>https://www.relataly.com/building-a-twitter-bot-for-trading-signals-using-python/3974/</link><guid isPermaLink="true">https://www.relataly.com/building-a-twitter-bot-for-trading-signals-using-python/3974/</guid><description>In this article, we will create a Twitter signal bot in Python that analyzes crypto prices for notable events and notifies users on Twitter.</description><pubDate>Wed, 19 May 2021 04:57:00 GMT</pubDate><category>Algorithmic Trading</category><category>Finance</category><category>Gate.io API</category><category>Python</category><category>Stock Market Forecasting</category><category>Time Series Forecasting</category><category>Twitter API</category></item><item><title>Requesting Crypto Price Data from the Gate.io REST API in Python</title><link>https://www.relataly.com/streaming-crypto-prices-via-the-gate-io-api-with-python/3982/</link><guid isPermaLink="true">https://www.relataly.com/streaming-crypto-prices-via-the-gate-io-api-with-python/3982/</guid><description>The Gate.io API provides access to market prices of a variety of cryptocurrencies. Learn to retrieve price data via the API using Python.</description><pubDate>Tue, 11 May 2021 07:17:14 GMT</pubDate><category>Finance</category><category>Gate.io API</category><category>Python</category><category>REST APIs</category></item><item><title>Posting Tweets On Twitter using Python and Tweepy</title><link>https://www.relataly.com/posting-tweets-on-twitter-using-python-and-tweepy/3925/</link><guid isPermaLink="true">https://www.relataly.com/posting-tweets-on-twitter-using-python-and-tweepy/3925/</guid><description>This article lays the foundation for building a Twitter bot by showing how to submit tweets via the Twitter API using Python and Tweepy.</description><pubDate>Sun, 09 May 2021 13:14:45 GMT</pubDate><category>REST APIs</category><category>Twitter API</category></item><item><title>Requesting Crypto Prices from the Coinmarketcap API using Python</title><link>https://www.relataly.com/requesting-crypto-price-data-from-the-coinmarketcap-api-using-python/3474/</link><guid isPermaLink="true">https://www.relataly.com/requesting-crypto-price-data-from-the-coinmarketcap-api-using-python/3474/</guid><description>Learn how to request crypto price data from the Coinmarketcap REST API and store it in a local SQLite DB using Python and Pewee.</description><pubDate>Sun, 18 Apr 2021 19:11:29 GMT</pubDate><category>Coinmarketcap API</category><category>REST APIs</category><category>SQLite</category><category>Stock Market Forecasting</category></item><item><title>Predictive Policing: Preventing Crime in San Francisco using XGBoost and Python</title><link>https://www.relataly.com/predicting-crimes-in-san-francisco-creatingsf-crime-map-using-xgboost/2960/</link><guid isPermaLink="true">https://www.relataly.com/predicting-crimes-in-san-francisco-creatingsf-crime-map-using-xgboost/2960/</guid><description>This article predicts crime types in San Francisco with the XGboost classifier in Python and displays them on a crime map of SF</description><pubDate>Sun, 07 Mar 2021 15:16:19 GMT</pubDate><category>Algorithms</category><category>Classification (multi-class)</category><category>Decision Trees</category><category>Fighting Crime</category><category>Gradient Boosting</category><category>Insurance</category><category>Kaggle Competitions</category><category>Machine Learning</category><category>mplleaflet</category><category>Python</category><category>Random Decision Forests</category><category>Scikit-Learn</category><category>Seaborn</category></item><item><title>Forecasting Beer Sales with ARIMA in Python</title><link>https://www.relataly.com/forecasting-beer-sales-with-arima-in-python/2884/</link><guid isPermaLink="true">https://www.relataly.com/forecasting-beer-sales-with-arima-in-python/2884/</guid><description>This Python tutorial shows how to use Auto-ARIMA for time series forecasting using the example of forecasting beer sales.</description><pubDate>Wed, 03 Feb 2021 21:23:08 GMT</pubDate><category>ARIMA</category><category>Logistics</category><category>Manufacturing</category><category>Python</category><category>Retail</category><category>Sales Forecasting</category><category>statsmodels</category><category>Stock Market Forecasting</category><category>Telecommunications</category><category>Time Series Forecasting</category><category>Use Cases</category></item><item><title>Color-Coded Cryptocurrency Price Charts in Python</title><link>https://www.relataly.com/cryptocurrency-price-charts-with-color-overlay-python/2820/</link><guid isPermaLink="true">https://www.relataly.com/cryptocurrency-price-charts-with-color-overlay-python/2820/</guid><description>Create color-coded cryptocurrency price charts with Python to visualize the lag between price points and the bitcoin halving.</description><pubDate>Tue, 19 Jan 2021 20:03:16 GMT</pubDate><category>Coinbase API</category><category>Correlation</category><category>Data Science</category><category>Data Sources</category><category>Data Visualization</category><category>Python</category><category>Seaborn</category><category>Stock Market Forecasting</category></item><item><title>Streaming Tweets and Images via the Twitter API in Python</title><link>https://www.relataly.com/accessing-twitter-data-via-the-twitter-rest-api/1976/</link><guid isPermaLink="true">https://www.relataly.com/accessing-twitter-data-via-the-twitter-rest-api/1976/</guid><description>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.</description><pubDate>Sun, 03 Jan 2021 20:46:47 GMT</pubDate><category>Data Science</category><category>Data Sources</category><category>Python</category><category>Twitter API</category></item><item><title>Image Classification with Convolutional Neural Networks - Classifying Cats and Dogs in Python</title><link>https://www.relataly.com/image-classification-with-deep-learning/2485/</link><guid isPermaLink="true">https://www.relataly.com/image-classification-with-deep-learning/2485/</guid><description>Learn about image classification with deep learning and develop a convolutional neural network that distinguishes between cats and dogs!</description><pubDate>Sun, 13 Dec 2020 13:09:31 GMT</pubDate><category>Classification (two-class)</category><category>Convolutional Neural Network (CNN)</category><category>Data Sources</category><category>Image Recognition</category><category>Keras</category><category>Neural Networks</category><category>Python</category><category>Tensorflow</category><category>Use Cases</category></item><item><title>Customer Churn Prediction - Understanding Models with Feature Permutation Importance using Python</title><link>https://www.relataly.com/predicting-the-customer-churn-of-a-telecommunications-provider/2378/</link><guid isPermaLink="true">https://www.relataly.com/predicting-the-customer-churn-of-a-telecommunications-provider/2378/</guid><description>This tutorial shows how to build a customer churn prediction model in telecommunications. We will use Python and measure feature importance.</description><pubDate>Sun, 02 Aug 2020 11:24:28 GMT</pubDate><category>Churn Prediction</category><category>Classification (two-class)</category><category>Data Science</category><category>Data Sources</category><category>Feature Permutation Importance</category><category>Hyperparameter Tuning</category><category>Machine Learning</category><category>Python</category><category>Random Decision Forests</category><category>Retail</category><category>Scikit-Learn</category><category>Seaborn</category><category>Use Cases</category></item><item><title>Tuning Model Hyperparameters with Grid Search at the Example of Training a Random Forest Classifier in Python</title><link>https://www.relataly.com/hyperparameter-tuning-with-grid-search/2261/</link><guid isPermaLink="true">https://www.relataly.com/hyperparameter-tuning-with-grid-search/2261/</guid><description>Learn how to tune the model hyperparameters of a Random Forest that predicts the survival of Titanic passengers using grid search in Python.</description><pubDate>Mon, 06 Jul 2020 19:16:52 GMT</pubDate><category>Classification (two-class)</category><category>Hyperparameter Tuning</category><category>Insurance</category><category>Logistics</category><category>Machine Learning</category><category>Python</category><category>Random Decision Forests</category><category>Risk Management</category><category>Scikit-Learn</category><category>Seaborn</category></item><item><title>Mastering Multivariate Stock Market Prediction with Python: A Guide to Effective Feature Engineering Techniques</title><link>https://www.relataly.com/feature-engineering-for-multivariate-time-series-models-with-python/1813/</link><guid isPermaLink="true">https://www.relataly.com/feature-engineering-for-multivariate-time-series-models-with-python/1813/</guid><description>Feature engineering for multivariate time series models using the example of stock market forecasting with Python and Keras Neural Networks.</description><pubDate>Mon, 29 Jun 2020 19:47:28 GMT</pubDate><category>Algorithms</category><category>Feature Engineering</category><category>Finance</category><category>Keras</category><category>Machine Learning</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Stock Market Forecasting</category><category>Tensorflow</category><category>Time Series Forecasting</category><category>Use Cases</category><category>Yahoo Finance API</category></item><item><title>Training a Sentiment Classifier with Naive Bayes and Logistic Regression in Python</title><link>https://www.relataly.com/simple-sentiment-analysis-using-naive-bayes-and-logistic-regression/2007/</link><guid isPermaLink="true">https://www.relataly.com/simple-sentiment-analysis-using-naive-bayes-and-logistic-regression/2007/</guid><description>This article deals with sentiment analysis and shows how to build a sentiment classifier using logistic regression and naive Bayes in Python.</description><pubDate>Sat, 20 Jun 2020 19:49:05 GMT</pubDate><category>Algorithms</category><category>Classification (multi-class)</category><category>Finance</category><category>Insurance</category><category>Logistic Regression</category><category>Machine Learning</category><category>Naive Bayes</category><category>Natural Language Processing</category><category>Python</category><category>Retail</category><category>Scikit-Learn</category><category>Seaborn</category><category>Sentiment Analysis</category><category>Telecommunications</category></item><item><title>Stock Market Prediction using Multivariate Time Series and Recurrent Neural Networks in Python</title><link>https://www.relataly.com/stock-market-prediction-using-multivariate-time-series-in-python/1815/</link><guid isPermaLink="true">https://www.relataly.com/stock-market-prediction-using-multivariate-time-series-in-python/1815/</guid><description>This tutorial shows how to model a multivariate time series using a recurrent neural network to forecast the stock market.</description><pubDate>Mon, 01 Jun 2020 15:20:46 GMT</pubDate><category>Algorithms</category><category>Finance</category><category>Keras</category><category>Machine Learning</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Stock Market Forecasting</category><category>Tensorflow</category><category>Time Series Forecasting</category><category>Use Cases</category></item><item><title>Classifying Purchase Intention of Online Shoppers with Python</title><link>https://www.relataly.com/predicting-the-purchase-intention-of-online-shoppers/982/</link><guid isPermaLink="true">https://www.relataly.com/predicting-the-purchase-intention-of-online-shoppers/982/</guid><description>Learn to use logistic regression to solve two-class prediction problems in Python by classifying online shoppers&apos; purchase intentions.</description><pubDate>Mon, 11 May 2020 19:42:35 GMT</pubDate><category>Algorithms</category><category>Classification (two-class)</category><category>Data Science</category><category>Data Sources</category><category>Feature Permutation Importance</category><category>Insurance</category><category>Kaggle Competitions</category><category>Logistic Regression</category><category>Machine Learning</category><category>Marketing Automation</category><category>Python</category><category>Retail</category><category>Sales Forecasting</category><category>Scikit-Learn</category><category>Seaborn</category></item><item><title>Measuring Regression Errors with Python</title><link>https://www.relataly.com/regression-error-metrics-python/923/</link><guid isPermaLink="true">https://www.relataly.com/regression-error-metrics-python/923/</guid><description>This tutorial presents six regression error metrics to measure model performance and shows how to implement them with Python and Scikit-learn</description><pubDate>Mon, 04 May 2020 07:34:09 GMT</pubDate><category>Algorithms</category><category>Data Science</category><category>Measuring Model Performance</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Synthetic Data</category><category>Time Series Forecasting</category></item><item><title>Rolling Time Series Forecasting: Creating a Multi-Step Prediction for a Rising Sine Curve using Neural Networks in Python</title><link>https://www.relataly.com/multi-step-time-series-forecasting-a-step-by-step-guide/275/</link><guid isPermaLink="true">https://www.relataly.com/multi-step-time-series-forecasting-a-step-by-step-guide/275/</guid><description>This article shows how to create a rolling multi-step forecast for a rising sine curve using Keras neural networks with lstm layers in Python</description><pubDate>Sun, 19 Apr 2020 07:59:49 GMT</pubDate><category>Algorithms</category><category>Data Science</category><category>Keras</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Synthetic Data</category><category>Tensorflow</category><category>Time Series Forecasting</category></item><item><title>Geographic Heat Maps with GeoPandas: Visualizing COVID-19 Data in Python</title><link>https://www.relataly.com/visualize-covid-19-data-on-a-geographic-heat-maps/291/</link><guid isPermaLink="true">https://www.relataly.com/visualize-covid-19-data-on-a-geographic-heat-maps/291/</guid><description>Geographic heat maps are powerful to visualize spatial data. Learn to use heat maps with Python and GeoPandas to visualize COVID-19 data</description><pubDate>Wed, 08 Apr 2020 20:03:00 GMT</pubDate><category>Data Science</category><category>Data Sources</category><category>Data Visualization</category><category>Geo Heat Maps</category><category>GeoPandas</category><category>Python</category></item><item><title>Correlation Matrix in Python: How Correlated are COVID-19 Cases and Different Financial Assets?</title><link>https://www.relataly.com/stock-market-correlation-matrix-in-python/103/</link><guid isPermaLink="true">https://www.relataly.com/stock-market-correlation-matrix-in-python/103/</guid><description>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.</description><pubDate>Sun, 05 Apr 2020 14:08:00 GMT</pubDate><category>Correlation</category><category>Data Science</category><category>Python</category><category>Seaborn</category><category>Stock Market Forecasting</category><category>Yahoo Finance API</category></item><item><title>Stock Market Prediction - Adjusting Time Series Prediction Intervals in Python</title><link>https://www.relataly.com/changing-prediction-intervals-for-time-series-forecasting-models/169/</link><guid isPermaLink="true">https://www.relataly.com/changing-prediction-intervals-for-time-series-forecasting-models/169/</guid><description>This tutorial shows how to adjust prediction intervals in time series forecasting using Keras recurrent neural networks and Python.</description><pubDate>Wed, 01 Apr 2020 14:37:56 GMT</pubDate><category>Algorithmic Trading</category><category>Algorithms</category><category>Finance</category><category>Keras</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Stock Market Forecasting</category><category>Tensorflow</category><category>Time Series Forecasting</category></item><item><title>Stock Market Prediction using Univariate Recurrent Neural Networks (RNN) with Python</title><link>https://www.relataly.com/univariate-stock-market-forecasting-using-a-recurrent-neural-network/122/</link><guid isPermaLink="true">https://www.relataly.com/univariate-stock-market-forecasting-using-a-recurrent-neural-network/122/</guid><description>This article shows how to train a univariate neural network model for stock market forecasting with Python and Scikit-learn.</description><pubDate>Mon, 23 Mar 2020 23:38:39 GMT</pubDate><category>Algorithms</category><category>Data Science</category><category>Finance</category><category>Keras</category><category>Neural Networks</category><category>Python</category><category>Recurrent Neural Networks</category><category>Stock Market Forecasting</category><category>Tensorflow</category><category>Time Series Forecasting</category><category>Use Cases</category></item><item><title>Accessing Remote Data Sources via REST APIs in Python</title><link>https://www.relataly.com/access-remote-data-sources-using-rest-apis-in-python/278/</link><guid isPermaLink="true">https://www.relataly.com/access-remote-data-sources-using-rest-apis-in-python/278/</guid><description>This article shows how to access remote data sources via REST APIs in Python. Two examples are given: Using Pandas Webreader and Requests.</description><pubDate>Sun, 01 Mar 2020 12:15:00 GMT</pubDate><category>Data Science</category><category>Data Sources</category><category>Python</category><category>Statworx COVID-19 API</category><category>Tech</category><category>Yahoo Finance API</category></item><item><title>Getting Started with the Anaconda Python Environment for Machine Learning</title><link>https://www.relataly.com/anaconda-python-environment-machine-learning/1663/</link><guid isPermaLink="true">https://www.relataly.com/anaconda-python-environment-machine-learning/1663/</guid><description>Get started with Python Machine Learning and set up the Anaconda Python Environment and Python packages, incl. Jupyter Notebooks.</description><pubDate>Fri, 14 Feb 2020 13:05:24 GMT</pubDate><category>Anaconda Environment</category><category>Data Science</category><category>Python</category></item><item><title>Flight Delay Prediction using Azure Machine Learning</title><link>https://www.relataly.com/predict-flight-delays-azure/57/</link><guid isPermaLink="true">https://www.relataly.com/predict-flight-delays-azure/57/</guid><description>Want to learn about flight delay prediction? This tutorial develops a classifier in Azure Machine Learning that predicts flight delays.</description><pubDate>Tue, 15 Oct 2019 16:10:23 GMT</pubDate><category>Algorithms</category><category>Azure Machine Learning</category><category>Classification (two-class)</category><category>Decision Trees</category><category>Logistics</category><category>Machine Learning</category><category>Risk Management</category><category>Use Cases</category></item></channel></rss>