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    • Simple Regression
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    • Clustering
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    • Logistic Regression
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  • Data Science
    • Exploratory Data Analysis
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    • Dimensionality Reduction
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    • Vector Databases
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    • Data Science Environments
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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
  • About
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Data Science Environments

A data science environment is a software environment that is specifically designed for data science and machine learning tasks. It typically includes a range of tools and libraries for data manipulation, analysis, visualization, and machine learning, as well as other tools and services that are commonly used in data science workflows. Data science environments are typically designed to be modular, so that different tools and libraries can be easily added, removed, or updated as needed. They may also include features such as integrated development environments (IDEs) and version control, to support collaboration and reproducibility in data science projects.

Getting Started with the Anaconda Python Environment for Machine Learning

February 26, 2023February 14, 2020

Anaconda is a popular open-source Python environment specifically designed for data science and machine learning. It comes with a range … Read more

flight delay prediction azure machine learning

Flight Delay Prediction using Azure Machine Learning

December 26, 2022October 15, 2019

If you travel a lot, you’ve probably already experienced this – you’re in a hurry on your way to the … Read more

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