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    690 Ergebnisse für „deep learning“

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      University of London

      Bachelor of Science in Computer Science

      Kompetenzen, die Sie erwerben: Computer Programming, Theoretical Computer Science, Web Development, Mathematics, Algorithms, Data Management, Databases, C Programming Language Family, Javascript, Software Engineering, C++ Programming, Programming Principles, Statistical Programming, Data Structures, Mathematical Theory & Analysis, Operating Systems, SQL, Computer Graphics, Machine Learning, Probability & Statistics, Computational Logic, Computer Architecture, Software Testing, Computer Networking, Human Computer Interaction, Security Engineering, Data Analysis, Python Programming, Agile Software Development, Network Security, Regression, Mobile Development, Software Architecture, Software Security, System Security, Algebra, Full-Stack Web Development, General Statistics, HTML and CSS, Interactive Design, Linear Algebra, Network Architecture, Network Model, Other Programming Languages, Probability Distribution, User Experience, Web Design, Design and Product, Product Design, Deep Learning, Data Visualization, Artificial Neural Networks, Back-End Web Development, Business Psychology, Calculus, Cloud Computing, Cloud Storage, Combinatorics, Computational Thinking, Computer Programming Tools, Database Design, Front-End Web Development, Graph Theory, Leadership and Management, Microarchitecture, Natural Language Processing, Professional Development, Research and Design, System Programming, User Experience Design, Internet Of Things, Journalism, Software Engineering Tools

      Erwerben Sie ein Zertifikat

      Degree · 1-4 Years

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      University of Colorado Boulder

      Master of Science in Data Science

      Kompetenzen, die Sie erwerben: Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Mathematics, Strategy and Operations, Computer Architecture, Databases, Leadership and Management, Communication, Hardware Design, Statistical Programming, Operating Systems, Machine Learning, Research and Design, Data Analysis, Finance, Computer Programming, Business Analysis, SQL, Writing, Regression, Data Structures, Project Management, Probability Distribution, Software Engineering, Business Communication, Entrepreneurship, Database Design, Statistical Tests, Statistical Analysis, Computer Graphics, Computer Networking, Design and Product, Accounting, Systems Design, Human Computer Interaction, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Statistical Machine Learning, PostgreSQL, Estimation, Data Visualization, Problem Solving, Operations Research, Internet Of Things, Network Architecture, Applied Mathematics, Computer Vision, Graph Theory, Deep Learning, Geometry, User Experience, Marketing, Computer Graphic Techniques, Mathematical Theory & Analysis, Programming Principles, Python Programming, Supply Chain and Logistics, Algebra, Cryptography, Business Psychology, Interactive Design, Critical Thinking, Security Engineering, Data Mining, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, User Experience Design, Cost Accounting, Differential Equations, Experiment, Cloud Computing, Cyberattacks, Computer Programming Tools, Computational Logic, Scrum (Software Development), Applied Machine Learning, Budget Management, Calculus, Econometrics, Feature Engineering, Graphic Design, Other Programming Languages, Sales, Software Architecture, Software Testing, System Programming, Visual Design, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Data Warehousing, Strategy, Basic Descriptive Statistics, Computational Thinking, Data Analysis Software, Exploratory Data Analysis, Investment Management, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Human Resources, Microarchitecture, Security Strategy, Application Development, Computer Security Models, Network Model, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Plot (Graphics), R Programming, Generally Accepted Accounting Principles (GAAP), Account Management, Banking, BlockChain, Business Process Management, C Programming Language Family, Contract Management, Data Architecture, FinTech, Financial Accounting, Financial Management, Geovisualization, Inventory Management, Management Accounting, Markov Model, Matlab, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Leadership Development, Network Analysis, Network Security, System Software

      Erwerben Sie ein Zertifikat

      Degree · 1-4 Years

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      University of Colorado Boulder

      Master of Engineering in Engineering Management

      Kompetenzen, die Sie erwerben: Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Mathematics, Strategy and Operations, Computer Architecture, Databases, Leadership and Management, Communication, Hardware Design, Statistical Programming, Operating Systems, Machine Learning, Research and Design, Data Analysis, Finance, Computer Programming, Business Analysis, SQL, Writing, Regression, Data Structures, Project Management, Probability Distribution, Software Engineering, Business Communication, Entrepreneurship, Database Design, Statistical Tests, Statistical Analysis, Computer Graphics, Computer Networking, Design and Product, Accounting, Systems Design, Human Computer Interaction, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Statistical Machine Learning, PostgreSQL, Estimation, Data Visualization, Problem Solving, Operations Research, Internet Of Things, Network Architecture, Applied Mathematics, Computer Vision, Graph Theory, Deep Learning, Geometry, User Experience, Marketing, Computer Graphic Techniques, Mathematical Theory & Analysis, Programming Principles, Python Programming, Supply Chain and Logistics, Algebra, Cryptography, Business Psychology, Interactive Design, Critical Thinking, Security Engineering, Data Mining, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, User Experience Design, Cost Accounting, Differential Equations, Experiment, Cloud Computing, Cyberattacks, Computer Programming Tools, Computational Logic, Scrum (Software Development), Applied Machine Learning, Budget Management, Calculus, Econometrics, Feature Engineering, Graphic Design, Other Programming Languages, Sales, Software Architecture, Software Testing, System Programming, Visual Design, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Data Warehousing, Strategy, Basic Descriptive Statistics, Computational Thinking, Data Analysis Software, Exploratory Data Analysis, Investment Management, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Human Resources, Microarchitecture, Security Strategy, Application Development, Computer Security Models, Network Model, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Plot (Graphics), R Programming, Generally Accepted Accounting Principles (GAAP), Account Management, Banking, BlockChain, Business Process Management, C Programming Language Family, Contract Management, Data Architecture, FinTech, Financial Accounting, Financial Management, Geovisualization, Inventory Management, Management Accounting, Markov Model, Matlab, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Leadership Development, Network Analysis, Network Security, System Software

      Erwerben Sie ein Zertifikat

      Degree · 1-4 Years

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      University of Colorado Boulder

      Master of Science in Electrical Engineering

      Kompetenzen, die Sie erwerben: Theoretical Computer Science, Probability & Statistics, General Statistics, Algorithms, Data Management, Mathematics, Strategy and Operations, Computer Architecture, Databases, Leadership and Management, Communication, Hardware Design, Statistical Programming, Operating Systems, Machine Learning, Research and Design, Data Analysis, Finance, Computer Programming, Business Analysis, SQL, Writing, Regression, Data Structures, Project Management, Probability Distribution, Software Engineering, Business Communication, Entrepreneurship, Database Design, Statistical Tests, Statistical Analysis, Computer Graphics, Computer Networking, Design and Product, Accounting, Systems Design, Human Computer Interaction, Data Model, Database Administration, Database Application, Database Theory, Machine Learning Algorithms, Statistical Machine Learning, PostgreSQL, Estimation, Data Visualization, Problem Solving, Operations Research, Internet Of Things, Network Architecture, Applied Mathematics, Computer Vision, Graph Theory, Deep Learning, Geometry, User Experience, Marketing, Computer Graphic Techniques, Mathematical Theory & Analysis, Programming Principles, Python Programming, Supply Chain and Logistics, Algebra, Cryptography, Business Psychology, Interactive Design, Critical Thinking, Security Engineering, Data Mining, Correlation And Dependence, Distributed Computing Architecture, Financial Analysis, Linear Algebra, Linux, User Experience Design, Cost Accounting, Differential Equations, Experiment, Cloud Computing, Cyberattacks, Computer Programming Tools, Computational Logic, Scrum (Software Development), Applied Machine Learning, Budget Management, Calculus, Econometrics, Feature Engineering, Graphic Design, Other Programming Languages, Sales, Software Architecture, Software Testing, System Programming, Visual Design, Artificial Neural Networks, Emotional Intelligence, Market Analysis, NoSQL, Statistical Visualization, Data Warehousing, Strategy, Basic Descriptive Statistics, Computational Thinking, Data Analysis Software, Exploratory Data Analysis, Investment Management, Material Handling, Organizational Development, Product Lifecycle, Risk Management, Amazon Web Services, Big Data, Cloud Platforms, Culture, Decision Making, Graphics Software, Human Resources, Microarchitecture, Security Strategy, Application Development, Computer Security Models, Network Model, Operational Analysis, Product Design, Reinforcement Learning, Software Security, System Security, User Research, Plot (Graphics), R Programming, Generally Accepted Accounting Principles (GAAP), Account Management, Banking, BlockChain, Business Process Management, C Programming Language Family, Contract Management, Data Architecture, FinTech, Financial Accounting, Financial Management, Geovisualization, Inventory Management, Management Accounting, Markov Model, Matlab, Natural Language Processing, Operations Management, Planning, Product Management, Spreadsheet Software, Storytelling, Supplier Relationship Management, Computer Science, Computer Security Incident Management, Data Science, Dimensionality Reduction, Forecasting, Journalism, Leadership Development, Network Analysis, Network Security, System Software

      Erwerben Sie ein Zertifikat

      Degree · 1-4 Years

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      Intel

      OpenVINO Beginner: Building a Crossroad AI Camera

      Kompetenzen, die Sie erwerben: Computer Vision, Internet Of Things

      Intermediate · Guided Project · Less Than 2 Hours

    • Kostenlos

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      IBM Skills Network

      데이터 과학이란 무엇인가?

      Kompetenzen, die Sie erwerben: Data Analysis, Big Data, Communication, Data Management, Data Mining, General Statistics, Probability & Statistics, Regression, Writing

      4.5

      (20 Bewertungen)

      Beginner · Course · 1-4 Weeks

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      IBM Skills Network

      ¿Qué es la ciencia de datos?

      Kompetenzen, die Sie erwerben: Data Analysis, Data Mining, Probability & Statistics, Regression

      4.7

      (312 Bewertungen)

      Beginner · Course · 1-4 Weeks

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      IBM Skills Network

      Introducción a la Ciencia de Datos

      Kompetenzen, die Sie erwerben: Statistical Programming, Data Analysis, Data Management, Databases, SQL, R Programming, Computer Programming, Data Mining, Data Model, Probability & Statistics, Regression, Web Development

      4.6

      (509 Bewertungen)

      Beginner · Specialization · 3-6 Months

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      IBM Skills Network

      Ciencia de Datos de IBM

      Kompetenzen, die Sie erwerben: Statistical Programming, Data Analysis, Computer Programming, Python Programming, Data Management, Databases, SQL, Probability & Statistics, Machine Learning, Computer Programming Tools, Data Visualization, Regression, Algorithms, Theoretical Computer Science, General Statistics, Mathematics, R Programming, Econometrics, Data Model, Data Mining, Machine Learning Algorithms, Web Development

      4.6

      (636 Bewertungen)

      Beginner · Professional Certificate · 3-6 Months

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      Kostenlos

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      Edge Impulse

      Introduction to Embedded Machine Learning

      Kompetenzen, die Sie erwerben: Applied Machine Learning, Machine Learning, Machine Learning Algorithms, Computer Programming

      4.8

      (480 Bewertungen)

      Intermediate · Course · 1-4 Weeks

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      Kostenlos

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      Deep Teaching Solutions

      Learning How to Learn: Powerful mental tools to help you master tough subjects

      Kompetenzen, die Sie erwerben: Personal Development, Business Psychology, Human Learning, Entrepreneurship, Collaboration, Decision Making, Problem Solving

      4.8

      (85.7k Bewertungen)

      Beginner · Course · 1-4 Weeks

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      Google Cloud

      Introduction to Trading, Machine Learning & GCP

      Kompetenzen, die Sie erwerben: Leadership and Management, Machine Learning, Finance, Cloud Computing, Cloud Platforms, Artificial Neural Networks, Entrepreneurship, Investment Management, Marketing, Sales, Strategy, Strategy and Operations

      4.0

      (773 Bewertungen)

      Intermediate · Course · 1-4 Weeks

    Suchanfragen mit Bezug zu deep learning

    deep learning specialization
    deep learning with pytorch : image segmentation
    deep learning for healthcare
    deep learning with pytorch : siamese network
    deep learning for business
    deep learning with pytorch : object localization
    deep learning with pytorch : generative adversarial network
    deep learning with pytorch : gradcam
    1…343536…58

    Zusammenfassend sind hier 10 unserer beliebtesten deep learning Kurse

    • Bachelor of Science in Computer Science: University of London
    • Master of Science in Data Science: University of Colorado Boulder
    • Master of Engineering in Engineering Management: University of Colorado Boulder
    • Master of Science in Electrical Engineering: University of Colorado Boulder
    • OpenVINO Beginner: Building a Crossroad AI Camera: Intel
    • 데이터 과학이란 무엇인가?: IBM Skills Network
    • ¿Qué es la ciencia de datos?: IBM Skills Network
    • Introducción a la Ciencia de Datos: IBM Skills Network
    • Ciencia de Datos de IBM: IBM Skills Network
    • Introduction to Embedded Machine Learning: Edge Impulse

    Fähigkeiten, die Sie bei Machine Learning erlernen können

    Python-Programmierung (33)
    TensorFlow (32)
    Deep Learning (30)
    Künstliches Neuronales Netz (24)
    Big Data (18)
    Statistische Klassifikation (17)
    Verstärkungslernen (13)
    Algebra (10)
    Bayes (10)
    Lineare Algebra (10)
    Lineare Regression (9)
    Numpy (9)

    Häufig gestellte Fragen zum Thema Deep Learning

    • 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.‎

    Diese häufig gestellten Fragen dienen nur zu Informationszwecken. Den Lernenden wird empfohlen, eingehender zu recherchieren, ob Kurse und andere angestrebte Qualifikationen wirklich ihren persönlichen, beruflichen und finanziellen Vorstellungen entsprechen.
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