Machine Learning Algorithms

Machine Learning Algorithms are computational procedures that allow computers to learn from data and make intelligent decisions or predictions. Coursera's Machine Learning Algorithms catalogue helps you understand, design and implement these algorithms for a wide range of applications. You'll learn about different types of machine learning techniques such as supervised, unsupervised, semi-supervised, and reinforcement learning, and get hands-on experience with algorithms like linear regression, neural networks, decision trees, k-means clustering, and many more. You’ll gain a solid foundation in Machine Learning Algorithms that will allow you to apply these techniques to real-world scenarios in various fields such as healthcare, finance, commerce, and technology.
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Results for "machine learning algorithms"

  • Status: Free Trial

    Alberta Machine Intelligence Institute

    Skills you'll gain: Supervised Learning, Feature Engineering, Responsible AI, Machine Learning Algorithms, Data Ethics, Applied Machine Learning, Data Quality, Data Processing, MLOps (Machine Learning Operations), Jupyter, Data Validation, Machine Learning, Business Operations, Data Cleansing, Product Lifecycle Management, Machine Learning Methods, Ethical Standards And Conduct, Classification And Regression Tree (CART), Test Data, Project Management

  • Status: New
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    Skills you'll gain: Data Science, Unsupervised Learning, Exploratory Data Analysis, Probability & Statistics, Machine Learning Algorithms, Applied Machine Learning, Classification And Regression Tree (CART), Data Analysis, Python Programming, Random Forest Algorithm, Dimensionality Reduction, Predictive Modeling, NumPy, Regression Analysis, Statistical Analysis, Data Processing, Deep Learning, Pandas (Python Package), Data Visualization, Data Manipulation

  • Status: New
    Status: Preview

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Regression Analysis, Applied Machine Learning, Statistical Modeling, Machine Learning Algorithms, PyTorch (Machine Learning Library), Statistical Methods, Statistical Machine Learning, Machine Learning, Predictive Analytics, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Unstructured Data, Probability & Statistics, Dimensionality Reduction, Algorithms

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    Skills you'll gain: Unsupervised Learning, Generative AI, Large Language Modeling, Supervised Learning, Deep Learning, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Reinforcement Learning, Statistical Machine Learning, Predictive Modeling, Machine Learning Algorithms, Artificial Neural Networks, Feature Engineering, Unstructured Data, Dimensionality Reduction, Performance Metric

What brings you to Coursera today?

  • Status: Free Trial

    Skills you'll gain: Exploratory Data Analysis, Feature Engineering, Unsupervised Learning, Supervised Learning, Regression Analysis, Dimensionality Reduction, Reinforcement Learning, Generative Model Architectures, Deep Learning, Data Analysis, Statistical Methods, Statistical Inference, Applied Machine Learning, Predictive Modeling, Statistical Hypothesis Testing, Data Processing, Machine Learning Algorithms, Machine Learning, Data Science, Python Programming

  • Status: Preview

    Sungkyunkwan University

    Skills you'll gain: Machine Learning Algorithms, Decision Tree Learning, Classification And Regression Tree (CART), Unsupervised Learning, Machine Learning, Supervised Learning, Python Programming, Algorithms, Linear Algebra, Bayesian Statistics, Probability

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    University of Washington

    Skills you'll gain: Regression Analysis, Applied Machine Learning, Feature Engineering, Machine Learning, Image Analysis, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Modeling, Artificial Intelligence, Deep Learning, Data Mining, Computer Vision, Statistical Machine Learning, Predictive Analytics, Text Mining, Machine Learning Algorithms, Big Data

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    Sungkyunkwan University

    Skills you'll gain: Machine Learning Algorithms, Machine Learning, Python Programming, Supervised Learning, Scikit Learn (Machine Learning Library), Applied Machine Learning, Regression Analysis, Data Analysis, Statistical Methods, Linear Algebra, Probability

  • Status: New
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    Skills you'll gain: Apache Spark, Keras (Neural Network Library), Deep Learning, Tensorflow, A/B Testing, Big Data, Data Ethics, Applied Machine Learning, Data Processing, Machine Learning Software, Artificial Neural Networks, Machine Learning Algorithms, Data Cleansing, Machine Learning, MLOps (Machine Learning Operations), Artificial Intelligence, Supervised Learning, Statistical Hypothesis Testing, Dimensionality Reduction, Reinforcement Learning

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    Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, AI Personalization, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms

What brings you to Coursera today?

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