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    • Deep Learning

    篩選依據

    ''deep learning'的 440 個結果

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      DeepLearning.AI

      Deep Learning

      您將獲得的技能: 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, 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, Natural Language, 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

      (134.1k 條評論)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI

      Neural Networks and Deep Learning

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

      4.9

      (114.7k 條評論)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      您將獲得的技能: Analysis, Applied Machine Learning, Artificial Neural Networks, Communication, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Deep Learning, Entrepreneurship, Forecasting, General Statistics, Machine Learning, Machine Learning Algorithms, Marketing, Modeling, Natural Language, Natural Language Processing, Probability & Statistics, Programming Principles, Python Programming, Statistical Machine Learning, Statistical Programming, Tensorflow, Time Series

      4.7

      (22.2k 條評論)

      Intermediate · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      Natural Language Processing

      您將獲得的技能: Algorithms, Artificial Neural Networks, Bayesian, Bayesian Statistics, Communication, Computer Graphics, Computer Programming, Deep Learning, Dimensionality Reduction, Experiment, General Statistics, Human Computer Interaction, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Natural Language, Natural Language Processing, Operations Research, Probability & Statistics, Process, Python Programming, Regression, Research and Design, Statistical Programming, Strategy and Operations, Supply Chain, Theoretical Computer Science, User Experience

      4.6

      (4.5k 條評論)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI,Stanford University

      Machine Learning

      您將獲得的技能: 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

      (1.9k 條評論)

      Beginner · Specialization · 1-3 Months

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      DeepLearning.AI

      TensorFlow: Advanced Techniques

      您將獲得的技能: Application Programming Interfaces, Applied Machine Learning, Artificial Neural Networks, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Networking, Computer Programming, Computer Vision, Deep Learning, Distributed Computing Architecture, Euler'S Totient Function, Machine Learning, Machine Learning Algorithms, Mathematics, Modeling, Network Architecture, Object Detection, Programming Principles, Python Programming, Statistical Programming, Tensorflow

      4.8

      (1.1k 條評論)

      Intermediate · Specialization · 3-6 Months

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      University of Colorado Boulder

      Introduction to Deep Learning

      您將獲得的技能: Applied Machine Learning, Deep Learning, Reinforcement Learning, Artificial Neural Networks, Machine Learning

      Intermediate · Course · 1-3 Months

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      IBM Skills Network

      IBM AI Engineering

      您將獲得的技能: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Big Data, Business Analysis, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Clustering Algorithms, Data Management, Data Structures, Databases, Deep Learning, Dimensionality Reduction, Econometrics, Entrepreneurship, General Statistics, Machine Learning, Machine Learning Algorithms, Mathematics, NoSQL, Probability & Statistics, Probability Distribution, Python Programming, Regression, SQL, Statistical Analysis, Statistical Machine Learning, Statistical Programming, Supply Chain Systems, Supply Chain and Logistics, Tensorflow, Theoretical Computer Science

      4.6

      (14.7k 條評論)

      Intermediate · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      Machine Learning Engineering for Production (MLOps)

      您將獲得的技能: 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

      (2.1k 條評論)

      Advanced · Specialization · 3-6 Months

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      Imperial College London

      Mathematics for Machine Learning

      您將獲得的技能: Algebra, Algorithms, Analysis, Artificial Neural Networks, Basic Descriptive Statistics, Calculus, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Analysis, Deep Learning, Differential Equations, General Statistics, Lambda Calculus, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Theory & Analysis, Mathematics, Matrices, Probability & Statistics, Probability Distribution, Python Programming, Regression, Statistical Programming, Theoretical Computer Science

      4.6

      (12.8k 條評論)

      Beginner · Specialization · 3-6 Months

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      DeepLearning.AI

      Generative Adversarial Networks (GANs)

      您將獲得的技能: Applied Machine Learning, Artificial Neural Networks, Bias, Computer Programming, Computer Vision, Deep Learning, Machine Learning, Machine Learning Algorithms, Modeling, Python Programming, Statistical Programming

      4.7

      (1.8k 條評論)

      Intermediate · Specialization · 1-3 Months

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      University of Toronto

      Self-Driving Cars

      您將獲得的技能: Artificial Neural Networks, Communication, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Decision Making, Deep Learning, Entrepreneurship, Estimation, Feature Engineering, General Statistics, Graph Theory, Leadership and Management, Linear Algebra, Machine Learning, Mathematical Theory & Analysis, Mathematics, Modeling, Planning, Probability & Statistics, Probability Distribution, Python Programming, Statistical Programming, Supply Chain and Logistics

      4.7

      (3.1k 條評論)

      Advanced · Specialization · 3-6 Months

    與 deep learning 相關的搜索

    deep learning specialization
    deep learning andrew ng
    deep learning with pytorch : image segmentation
    deep learning for business
    deep learning for healthcare
    deep learning with pytorch : neural style transfer
    deep learning and reinforcement learning
    deep learning with pytorch : siamese network
    1234…37

    總之,這是我們最受歡迎的 deep learning 門課程中的 10 門

    • Deep Learning: DeepLearning.AI
    • Neural Networks and Deep Learning: DeepLearning.AI
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • Natural Language Processing: DeepLearning.AI
    • Machine Learning: DeepLearning.AI
    • TensorFlow: Advanced Techniques: DeepLearning.AI
    • Introduction to Deep Learning: University of Colorado Boulder
    • IBM AI Engineering: IBM Skills Network
    • Machine Learning Engineering for Production (MLOps): DeepLearning.AI
    • Mathematics for Machine Learning: Imperial College London

    您可以在 Machine Learning 中學到的技能

    Python 程序設計 (33)
    Tensorflow (32)
    人工神經網絡 (24)
    大數據 (18)
    統計分類 (17)
    強化學習 (13)
    代數 (10)
    貝葉斯定理 (10)
    線性代數 (10)
    線性回歸 (9)
    Numpy (9)

    關於 深度學習 的常見問題

    • Deep learning is a powerful application of machine learning (ML) algorithms modeled after biological systems of information processing called artificial neural networks (ANN). Machine learning is an artificial intelligence (AI) technique that allows computers to automatically learn from data without explicit programming, and deep learning harnesses multiple layers of interconnected neural networks to generate more sophisticated insights.

      While this field of computer science is quite new, it is already being used in a growing range of important applications. Deep learning excels at automated image recognition, also known as computer vision, which is used for creating accurate facial recognition systems and safely driving autonomous vehicles. This approach is also used for speech recognition and natural language processing (NLP) applications, which allow for computers to interact with human users via voice commands.

      Machine learning algorithms such as logistic regression are key to creating deep learning applications, along with commonly used programming languages such as Tensorflow and Python. These programming languages are generally preferred for teaching and learning in this field due to their flexibility and relative accessibility - an important priority given the relevance of deep learning to a wide range of professionals without a computer science background.‎

    • A familiarity with the capabilities and development process for deep learning applications can be an asset in a growing number of careers. For example, the use of deep learning is being explored in healthcare for automatic reading of radiology images, as well as searching for patterns in genes and pharmaceutical interactions that can aid in the discovery of new types of medicines. In many fields, even a basic understanding of deep learning can help professionals identify new potential applications of this powerful technology.

      Those with a deeper expertise in deep learning may become computer research scientists in this field, responsible for inventing new algorithms and finding new applications for these techniques. Given the wide range of uses for deep learning, computer scientists in this field are in high demand for jobs at private companies as well as government agencies and research universities. According to the Bureau of Labor Statistics, computer research scientists earned a median annual salary of $122,840 as of 2019, and these jobs are expected to grow much faster than average.‎

    • Certainly - in fact, Coursera is one of the best places to learn about deep learning. Through partnerships with deeplearning.ai and Stanford University, Coursera offers courses as well as Specializations taught by some of the pioneering thinkers and educators in this field. You can also learn via courses and Specializations from industry leaders such as Google Cloud and Intel, or get a professional certificate from IBM. Guided Projects also offer an opportunity to build skills in deep learning through hands-on tutorials led by experienced instructors, allowing you to learn with confidence.‎

    • The skills or experience you may need to have before studying deep learning, and which can help you better understand an advanced concept such as deep learning, can include sign language reading, music generation, and natural language processing (NLP), in addition to many others. If you have knowledge of Python 3 and understand the basic concepts of general machine-learning algorithms and deep learning, you may have the necessary skills to learn this specialization. You may also want to know about probability and statistics to study deep learning concepts. Basic math, such as algebra and calculus, is also an important prerequisite to deep learning because it relates to machine learning and data science. Also, if you have worked in the tech or artificial intelligence (AI) fields, you may have the necessary experience to study deep learning.‎

    • The type of person who is best suited to study deep learning is someone comfortable working with statistics, programming, advanced calculus, advanced algebra, and engineering. Deep learning benefits someone passionate about working in the AI fields which can create types of deep learning networks that help machines perform human functions. A person best suited to learn about deep learning has a vested interest in understanding how the intelligence is built to run everything from driverless cars, mobile devices, stock trading systems, and robotic surgery equipment, for example. Deep learning benefits someone with a goal of working with systems such as computer vision, speech recognition, NLP, audio recognition bioinformatics systems, and medical image analysis.‎

    • Deep learning may be right for you if you want to break into AI. The specialization may benefit you if you are a machine learning researcher or practitioner who is seeking to learn the next generation of machine learning, and you want to develop practical skills in the popular deep learning framework TensorFlow. Deep learning is one of the most highly sought-after skills in tech, and mastering it may lead you to many opportunities in the field of AI. It may also benefit you if you want to learn how to build neural networks and how to lead successful machine learning projects, and if you have a passion for learning about convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and how to master concepts in Python and TensorFlow.‎

    此常見問題解答內容僅供參考。建議學生多做研究,確保所追求的課程和其他證書符合他們的個人、專業和財務目標。
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