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온라인 학위경력 찾기기업용 Coursera대학교용
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    • Machine Learning Andrew Ng

    필터링 기준

    "machine learning andrew ng"에 대한 46개의 결과

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      DeepLearning.AI, Stanford University

      Machine Learning

      획득할 기술: Accounting, Algorithms, Applied Machine Learning, Artificial Neural Networks, Calculus, Communication, Computer Programming, Computer Vision, Cost, Data Analysis, Data Management, Data Mining, Data Structures, Deep Learning, Econometrics, Feature Engineering, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Operations Research, Probability & Statistics, Probability Distribution, Python Programming, Regression, Reinforcement Learning, Research and Design, Statistical Classification, Statistical Machine Learning, Statistical Programming, Strategy and Operations, Tensorflow, Theoretical Computer Science

      4.9

      (2.2k개의 검토)

      Beginner · Specialization · 1-3 Months

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      DeepLearning.AI

      Unsupervised Learning, Recommenders, Reinforcement Learning

      획득할 기술: Algorithms, General Statistics, Research and Design, Computer Programming, Mathematical Theory & Analysis, Theoretical Computer Science, Tensorflow, Machine Learning, Python Programming, Data Mining, Mathematics, Probability & Statistics, Statistical Programming, Communication, Machine Learning Algorithms, Applied Machine Learning, Artificial Neural Networks, Data Analysis, Operations Research, Strategy and Operations, Probability Distribution, Reinforcement Learning

      5.0

      (83개의 검토)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      Deep Learning

      획득할 기술: Advertising, Algorithms, Analysis, Applied Machine Learning, Artificial Neural Networks, Bayesian Statistics, Big Data, Business Psychology, Communication, Computational Logic, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Networking, Computer Programming, Computer Vision, Data Management, Decision Making, Deep Learning, Entrepreneurship, General Statistics, Hardware Design, Human Computer Interaction, Interactive Design, Leadership and Management, Linear Algebra, Machine Learning, Machine Learning Algorithms, Marketing, Markov Model, Mathematical Theory & Analysis, Mathematics, Modeling, Natural Language Processing, Network Architecture, Network Model, Probability & Statistics, Project Management, Python Programming, Regression, Sales, Statistical Machine Learning, Statistical Programming, Strategy, Strategy and Operations, Supply Chain, Supply Chain Systems, Supply Chain and Logistics, Tensorflow, Theoretical Computer Science, User Experience

      4.8

      (134.2k개의 검토)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI

      Supervised Machine Learning: Regression and Classification

      획득할 기술: Theoretical Computer Science, Cost, Computer Programming, Statistical Machine Learning, Accounting, Econometrics, Machine Learning, Regression, Logistic Regression, Probability & Statistics, Feature Engineering, Algorithms, Linear Algebra, Mathematics, Linearity, Python Programming, Artificial Neural Networks, General Statistics, Linear Regression, Statistical Classification, Calculus, Probability Distribution, Statistical Programming, Machine Learning Algorithms, Applied Machine Learning

      4.9

      (2k개의 검토)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      AI For Everyone

      획득할 기술: Machine Learning, Artificial Neural Networks, Ethics, Deep Learning, Machine Learning Algorithms

      4.8

      (36.3k개의 검토)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      Advanced Learning Algorithms

      획득할 기술: Statistical Machine Learning, Probability & Statistics, Computer Programming, General Statistics, Machine Learning, Theoretical Computer Science, Artificial Neural Networks, Mathematics, Data Management, Deep Learning, Tensorflow, Python Programming, Machine Learning Algorithms, Linear Algebra, Applied Machine Learning, Statistical Programming, Data Structures, Decision Tree, Probability Distribution, Computer Vision

      4.9

      (363개의 검토)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      Machine Learning Engineering for Production (MLOps)

      획득할 기술: Applied Machine Learning, Business Analysis, Change Management, Cloud Computing, Computer Networking, Computer Programming, Data Analysis, Data Management, Data Visualization, Deep Learning, DevOps, Estimation, Exploratory Data Analysis, Extract, Transform, Load, Feature Engineering, General Statistics, Leadership and Management, Machine Learning, Machine Learning Algorithms, Modeling, Network Security, Probability & Statistics, Python Programming, Security Engineering, Security Strategy, Statistical Programming, Statistical Visualization, Strategy and Operations, Tensorflow

      4.7

      (2.2k개의 검토)

      Advanced · Specialization · 3-6 Months

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      DeepLearning.AI

      Neural Networks and Deep Learning

      획득할 기술: Markov Model, Business Psychology, General Statistics, Mathematical Theory & Analysis, Theoretical Computer Science, Entrepreneurship, Logistic Regression, Bayesian Statistics, Probability & Statistics, Regression, Mathematics, Network Model, Computer Networking, Machine Learning, Computer Programming, Linear Algebra, Supply Chain and Logistics, Algorithms, Applied Machine Learning, Artificial Neural Networks, Python Programming, Computer Architecture, Supply Chain, Numpy, Hardware Design, Deep Learning, Computational Logic, Supply Chain Systems, Machine Learning Algorithms

      4.9

      (114.8k개의 검토)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

      획득할 기술: Computer Programming, Computer Graphics, Computer Graphic Techniques, Tensorflow, Applied Machine Learning, Artificial Neural Networks, Python Programming, Keras, Machine Learning, Programming Principles, Statistical Programming, Deep Learning, Convolutional Neural Network, Computer Vision

      4.7

      (17.5k개의 검토)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      Convolutional Neural Networks

      획득할 기술: Keras, Machine Learning, Computer Programming, Computer Graphics, Computer Networking, Computer Graphic Techniques, Computer Architecture, Object Detection, Tensorflow, Python Programming, Network Architecture, Convolutional Neural Network, Applied Machine Learning, Statistical Programming, Artificial Neural Networks, Deep Learning, Computer Vision

      4.9

      (40.6k개의 검토)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      Introduction to Machine Learning in Production

      획득할 기술: Leadership and Management, Data Management, Machine Learning, Modeling, General Statistics, Machine Learning Algorithms, Probability & Statistics, Applied Machine Learning, Estimation, Change Management, Strategy and Operations

      4.8

      (1.8k개의 검토)

      Advanced · Course · 1-4 Weeks

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      DeepLearning.AI

      TensorFlow: Data and Deployment

      획득할 기술: Android Development, Application Development, Applied Machine Learning, Computer Architecture, Computer Programming, Computer Vision, Cross Platform Development, Data Management, Data Model, Data Visualization, Deep Learning, Entrepreneurship, Extract, Transform, Load, HTML and CSS, Javascript, Leadership and Management, Machine Learning, Machine Learning Algorithms, Machine Learning Software, Marketing, Microarchitecture, Mobile Development, Mobile Development Tools, Modeling, Problem Solving, Python Programming, Research and Design, Security Engineering, Software Engineering, Statistical Programming, Swift Programming, Tensorflow, Theoretical Computer Science, Visualization (Computer Graphics), Web Development, iOS Development

      4.6

      (1.3k개의 검토)

      Intermediate · Specialization · 3-6 Months

    1234

    요약하자면, 여기에 가장 인기 있는 machine learning andrew ng 강좌 10개가 있습니다.

    • Machine Learning: DeepLearning.AI
    • Unsupervised Learning, Recommenders, Reinforcement Learning: DeepLearning.AI
    • Deep Learning: DeepLearning.AI
    • Supervised Machine Learning: Regression and Classification: DeepLearning.AI
    • AI For Everyone: DeepLearning.AI
    • Advanced Learning Algorithms: DeepLearning.AI
    • Machine Learning Engineering for Production (MLOps): DeepLearning.AI
    • Neural Networks and Deep Learning: DeepLearning.AI
    • Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning: DeepLearning.AI
    • Convolutional Neural Networks: DeepLearning.AI

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