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    • Deep Learning

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    「deep learning」の692件の結果

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      University of Colorado Boulder

      Introduction to Deep Learning

      習得できるスキル: Deep Learning, Machine Learning, Artificial Neural Networks, Applied Machine Learning, Machine Learning Algorithms, Reinforcement Learning

      3.3

      (6件のレビュー)

      Intermediate · Course · 1-3 Months

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      Google Cloud

      Machine Learning on Google Cloud

      習得できるスキル: Machine Learning, Cloud Computing, Computer Programming, Statistical Programming, Python Programming, Applied Machine Learning, Feature Engineering, Google Cloud Platform, Tensorflow, Deep Learning, Probability & Statistics, Data Analysis, Entrepreneurship, Artificial Neural Networks, Computer Architecture, Data Visualization, Exploratory Data Analysis, Regression, SQL, Statistical Visualization, Data Science, Apache, Basic Descriptive Statistics, Bayesian Statistics, Computational Thinking, Data Management, Distributed Computing Architecture, General Statistics, Hardware Design, Machine Learning Algorithms, Machine Learning Software, Statistical Machine Learning, Theoretical Computer Science, Algorithms, Business Analysis, Business Psychology, Data Analysis Software, Dimensionality Reduction, Full-Stack Web Development, Information Technology, Natural Language Processing, Statistical Analysis, Web Development

      4.5

      (9.4k件のレビュー)

      Intermediate · Specialization · 3-6 Months

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      IBM Skills Network

      Machine Learning Introduction for Everyone

      習得できるスキル: Machine Learning, Algorithms, Data Analysis, Deep Learning, Machine Learning Algorithms, Probability & Statistics, Regression, Reinforcement Learning, Theoretical Computer Science

      4.5

      (94件のレビュー)

      Beginner · Course · 1-4 Weeks

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      Coursera Project Network

      Deep Learning with PyTorch : Siamese Network

      習得できるスキル: Artificial Neural Networks, Deep Learning, Machine Learning, Computer Vision

      4.4

      (13件のレビュー)

      Advanced · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Deep Learning with PyTorch : Image Segmentation

      習得できるスキル: Computer Programming, Computer Vision, Deep Learning, Machine Learning, Python Programming, Statistical Programming

      4.2

      (71件のレビュー)

      Intermediate · Guided Project · Less Than 2 Hours

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      DeepLearning.AI

      AI for Medicine

      習得できるスキル: Machine Learning, Machine Learning Algorithms, Python Programming, Deep Learning, Machine Learning Software, Statistical Programming, General Statistics, Artificial Neural Networks, Computer Vision, Data Analysis, Probability & Statistics, Algorithms, Applied Machine Learning, Basic Descriptive Statistics, Estimation, Exploratory Data Analysis, Natural Language Processing, Plot (Graphics), Scientific Visualization, Statistical Tests, Statistical Visualization, Theoretical Computer Science, Computer Graphic Techniques, Computer Graphics, Computer Programming, Data Management, Data Structures, Feature Engineering

      4.7

      (2.1k件のレビュー)

      Intermediate · Specialization · 1-3 Months

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      Duke University

      AI Product Management

      習得できるスキル: Machine Learning, Machine Learning Algorithms, Applied Machine Learning, Probability & Statistics, Regression, Human Computer Interaction, Data Analysis, Data Mining, Deep Learning, Leadership and Management, Business Psychology, Computer Networking, Database Administration, Databases, Finance, Network Security, Regulations and Compliance, Research and Design, Security Engineering, User Experience, User Experience Design, Artificial Neural Networks, Computer Vision, Natural Language Processing, Statistical Machine Learning, Algorithms, Data Management, Data Science, Data Structures, Design and Product, Econometrics, Entrepreneurship, Feature Engineering, General Statistics, Operating Systems, Product Management, Project Management, Strategy and Operations, Systems Design, Theoretical Computer Science

      4.6

      (167件のレビュー)

      Beginner · Specialization · 3-6 Months

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      Coursera Project Network

      Deep Learning with PyTorch : Generative Adversarial Network

      習得できるスキル: Computer Programming, Deep Learning, Machine Learning, Machine Learning Algorithms, Python Programming, Statistical Programming, Tensorflow

      4.6

      (40件のレビュー)

      Intermediate · Guided Project · Less Than 2 Hours

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      University of Michigan

      Financial Technology (Fintech) Innovations

      習得できるスキル: Finance, FinTech, BlockChain, Investment Management, Banking, Leadership and Management, Payments, Accounting, Big Data, Business Analysis, Corporate Accouting, Data Analysis, Data Management, Deep Learning, Financial Analysis, Machine Learning, Probability & Statistics, Regression

      4.7

      (2.2k件のレビュー)

      Beginner · Specialization · 3-6 Months

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      MathWorks

      Computer Vision for Engineering and Science

      習得できるスキル: Computer Vision, Machine Learning, Data Analysis, Matlab

      5.0

      (6件のレビュー)

      Intermediate · Specialization · 1-3 Months

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      University of Illinois at Urbana-Champaign

      Deep Learning Methods for Healthcare

      Advanced · Course · 1-4 Weeks

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      University of Colorado Boulder

      Machine Learning: Theory and Hands-on Practice with Python

      習得できるスキル: Machine Learning, Statistical Machine Learning, Machine Learning Algorithms, Probability & Statistics, Python Programming, Statistical Programming, Regression, Deep Learning, Data Analysis, Artificial Neural Networks, Applied Machine Learning, Correlation And Dependence, Statistical Analysis, Statistical Tests, Exploratory Data Analysis, Algorithms, Reinforcement Learning, Theoretical Computer Science, Basic Descriptive Statistics, Data Mining, Feature Engineering, General Statistics, Natural Language Processing, Data Management, Data Structures, Dimensionality Reduction

      3.1

      (27件のレビュー)

      Intermediate · Specialization · 3-6 Months

    deep learningに関連する検索

    deep learning specialization
    deep learning with pytorch : image segmentation
    deep learning for healthcare
    deep learning with pytorch : siamese network
    deep learning with pytorch : object localization
    deep learning with pytorch : generative adversarial network
    deep learning with pytorch : gradcam
    deep learning and reinforcement learning
    1234…58

    要約して、deep learning の人気コース10選をご紹介します。

    • Introduction to Deep Learning: University of Colorado Boulder
    • Machine Learning on Google Cloud: Google Cloud
    • Machine Learning Introduction for Everyone: IBM Skills Network
    • Deep Learning with PyTorch : Siamese Network: Coursera Project Network
    • Deep Learning with PyTorch : Image Segmentation: Coursera Project Network
    • AI for Medicine: DeepLearning.AI
    • AI Product Management: Duke University
    • Deep Learning with PyTorch : Generative Adversarial Network: Coursera Project Network
    • Financial Technology (Fintech) Innovations: University of Michigan
    • Computer Vision for Engineering and Science: MathWorks

    Machine Learningで学べるスキル

    Pythonプログラミング (33)
    TensorFlow (32)
    ディープラーニング (30)
    人工ニューラルネットワーク (24)
    ビッグデータ (18)
    統計的分類 (17)
    強化学習 (13)
    代数 (10)
    ベイズ (10)
    線型代数学 (10)
    線形回帰 (9)
    NumPy (9)

    ディープラーニングに関するよくある質問

    • 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.‎

    このFAQの内容は、情報提供のみを目的としています。受講生は、自分の個人的、職業的、経済的な目標に合ったコースやその他の資格を取得するために、さらに調べることをお勧めします。
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