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  • Machine Learning
    • 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
    • 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
    • SQLite
    • Data Science Environments
      • Anaconda
      • Azure Machine Learning
    • Python Libraries
      • Scikit-Learn
      • Tensorflow
      • Keras
      • Pytorch
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      • OpenAI Gym
      • Seaborn
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      • Facebook Prophet
      • GeoPandas
  • Data Sources
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    • REST APIs
    • 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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Chart Analysis

Chart analysis is the process of examining stock, commodity, or other market charts, using technical analysis techniques, to identify trends and patterns that may provide insight into future market movements. Chart analysis is often used by traders and investors to make buy and sell decisions, based on the assumption that historical market data can provide clues about future market behavior. Chart analysis typically involves the use of various indicators, such as moving averages and oscillators, to help identify trends, support and resistance levels, and other key factors that may affect the price of an asset. Chart analysis can be a useful tool for traders and investors, but it is not a guarantee of future performance, and it is important to use it in combination with other forms of analysis and research.

Color-Coded Cryptocurrency Price Charts in Python

March 5, 2023January 19, 2021
color cryptocurrency price charts bitcoin python relataly midjourney api-min

The rapid rise in the price of Bitcoin and other cryptocurrencies has led to increased interest in analyzing and visualizing … Read more

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