Machine Learning

Machine Learning is a branch of artificial intelligence that automates analytical model building, enabling systems to learn and improve from experience without being explicitly programmed. Coursera's Machine Learning catalogue empowers you to understand, design, and apply powerful algorithms and statistical models to make predictions or decisions without human intervention. You'll learn about various forms of learning, such as supervised, unsupervised, and reinforcement learning, along with techniques such as regression, classification, clustering, and deep learning. Furthermore, you'll gain insights into the ethical and societal considerations of Machine Learning and its applications across various industries like healthcare, finance, and entertainment.

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Results for "Machine Learning"

  • Multiple educators

    Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Training, Applied Machine Learning, Machine Learning Algorithms, Transfer Learning, Machine Learning, Jupyter, Data Ethics, Decision Tree Learning, Model Evaluation, Responsible AI, Tensorflow, Scikit Learn (Machine Learning Library), NumPy, Predictive Modeling, Deep Learning, Artificial Intelligence, Classification Algorithms, Reinforcement Learning

  • Skills you'll gain: Supervised Learning, Applied Machine Learning, Jupyter, Scikit Learn (Machine Learning Library), Machine Learning, Model Training, NumPy, Machine Learning Algorithms, Predictive Modeling, Classification Algorithms, Feature Engineering, Artificial Intelligence, Model Evaluation, Data Preprocessing, Python Programming, Logistic Regression, Model Optimization, Regression Analysis, Algorithms

  • Skills you'll gain: Unsupervised Learning, Supervised Learning, Model Evaluation, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Methods, Applied Machine Learning, Model Training, Predictive Modeling, Machine Learning Algorithms, Statistical Methods, Machine Learning, Dimensionality Reduction, Python Programming, Logistic Regression, Model Optimization, Classification Algorithms

  • Skills you'll gain: MLOps (Machine Learning Operations), Model Evaluation, PyTorch (Machine Learning Library), Responsible AI, Debugging, Model Deployment, Model Training, Model Optimization, Deep Learning, Test Tools, Applied Machine Learning, Testability, Machine Learning Methods, Machine Learning, Data Preprocessing, Verification And Validation, Python Programming, AI Security, Test Driven Development (TDD), AI Enablement

  • University of Washington

    Skills you'll gain: Model Evaluation, Classification Algorithms, Regression Analysis, Applied Machine Learning, Machine Learning Methods, Feature Engineering, Machine Learning, Image Analysis, Machine Learning Algorithms, AI Personalization, Unsupervised Learning, Predictive Modeling, Classification And Regression Tree (CART), Supervised Learning, Bayesian Statistics, Statistical Machine Learning, Model Training, Logistic Regression, Statistical Modeling, Data Mining

  • Skills you'll gain: Unsupervised Learning, Exploratory Data Analysis, Feature Engineering, Dimensionality Reduction, Supervised Learning, Classification Algorithms, Regression Analysis, Scikit Learn (Machine Learning Library), Machine Learning Algorithms, Statistical Methods, Data Preprocessing, Applied Machine Learning, Model Evaluation, Statistical Inference, Predictive Modeling, Machine Learning Methods, Statistical Hypothesis Testing, Model Training, Data Processing, Machine Learning

  • Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Statistical Methods, Probability Distribution, Linear Algebra, Statistical Inference, Model Optimization, Machine Learning Methods, Statistics, Applied Mathematics, Probability, Calculus, Dimensionality Reduction, Applied Machine Learning, Mathematical Software, Data Transformation, Machine Learning

  • Skills you'll gain: Model Evaluation, Predictive Modeling, Model Training, Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Supervised Learning, Applied Machine Learning, Machine Learning Algorithms, Artificial Intelligence, Deep Learning, Classification Algorithms, Unsupervised Learning, Regression Analysis, Reinforcement Learning

  • Skills you'll gain: Model Deployment, MLOps (Machine Learning Operations), Application Deployment, Model Training, Continuous Deployment, Model Evaluation, Data Preprocessing, Model Optimization, Machine Learning, Applied Machine Learning, Data Validation, Data Integrity, Data Maintenance, Data Quality, Data Synthesis, Data Collection, System Monitoring, Continuous Monitoring, Unstructured Data

  • Skills you'll gain: PyTorch (Machine Learning Library), Logistic Regression, Machine Learning Methods, Transfer Learning, Reinforcement Learning, Convolutional Neural Networks, Deep Learning, Image Analysis, Applied Machine Learning, Model Training, Natural Language Processing, Machine Learning, Model Optimization, Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

  • University of London

    Skills you'll gain: Model Training, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Feature Engineering, Machine Learning, Artificial Intelligence, Statistical Machine Learning, Model Evaluation, Data Literacy, Machine Learning Algorithms, AI literacy, Responsible AI, Data Collection

  • Skills you'll gain: Model Training, Machine Learning Algorithms, Transfer Learning, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Model Evaluation, Tensorflow, Responsible AI, Supervised Learning, Deep Learning, Classification Algorithms, Random Forest Algorithm, Model Optimization, Artificial Neural Networks, Logistic Regression, Regression Analysis