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    • Classification: Two Class
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  • About

relataly.com

  • AI
    • Simple Regression
    • Classification: Two Class
    • Classification: Multi-Class
    • Clustering
    • Time Series Forecasting
    • Anomaly Detection
    • Natural Language
    • Recommender Systems
    • Reinforcement Learning
    • Responsible AI
  • Use Cases
    • Stock Market Forecasting
    • Algorithmic Trading
    • Sentiment Analysis
    • Churn Prediction
    • Fraud Detection
    • Predictive Maintenance
    • Marketing Automation
    • Customer Segmentation
    • Sales Forecasting
    • ChatBots
    • Fighting Crime
    • Risk Management
    • Image Recognition
  • Algorithms
    • CNNs
    • RNNs (LSTM)
    • Decision Trees
    • Random Decision Forests
    • Random Isolation Forest
    • Local Outlier Factor
    • Gradient Boosting
    • Collaborative Filtering
    • Content-based Filtering
    • K-Nearest Neighbors
    • K-Means
    • Affinity Propagation
    • Agglomerative Clustering
    • Logistic Regression
    • Naive Bayes
    • ARIMA
  • Data Science
    • Exploratory Data Analysis
    • Feature Engineering
    • Hyperparameter Tuning
    • Dimensionality Reduction
    • Model Interpretation
    • Data Visualization
    • Correlation
    • Measuring Performance
    • Cross-Validation
    • Vector Databases
    • SQLite
    • Data Science Environments
      • Anaconda
      • Azure Machine Learning
    • Python Libraries
      • Scikit-Learn
      • Tensorflow
      • Keras
      • Pytorch
      • PySpark
      • Chainer
      • OpenAI Gym
      • Seaborn
      • Fairlearn
      • Facebook Prophet
      • GeoPandas
  • Data & APIs
    • OpenAI API
    • REST APIs
    • NewsAPI
    • Coinmarketcap API
    • Coinbase API
    • Gate.io API
    • Yahoo Finance API
    • Statworx COVID-19 API
    • Twitter API
    • Reddit API
    • Kaggle Competitions
    • Synthetic Data
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AI in E-Commerce

The role of AI in e-commerce is to use artificial intelligence technologies to automate and improve various aspects of online retail. AI can be used in e-commerce to provide personalized recommendations to customers based on their browsing and purchase history, to automatically classify and organize products, and to identify potential fraud and security threats. AI can also be used to automate customer service tasks, such as answering common questions and providing support. For example, AI-powered chatbots can interact with customers in real-time, providing fast and efficient service. In addition, AI can be used to optimize the design and functionality of e-commerce websites, making them more user-friendly and efficient. Overall, the use of AI in e-commerce has the potential to improve the customer experience, increase sales, and reduce operational costs.

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Build a High-Performing Movie Recommender System using Collaborative Filtering in Python

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The digital age presents us with an unmanageable number of decisions and even more options. Which series to watch today? … Read more

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Automate Crypto Trading with a Python-Powered Twitter Bot and Gate.io Signals

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This tutorial develops a Twitter bot in Python that will generate automated trading signals. The bot will pull real-time price … Read more

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In a previous article, we have shown how to retrieve social media data via the Twitter API in Python. However, … Read more

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Forecasting Beer Sales with ARIMA in Python

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