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    • Reinforcement Learning

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    48 resultados para "reinforcement learning"

    • University of Alberta

      University of Alberta

      Reinforcement Learning

      Habilidades que obtendrás: Artificial Neural Networks, Entrepreneurship, Euler'S Totient Function, Leadership and Management, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Operations Research, Planning, Reinforcement Learning, Research and Design, Strategy and Operations, Supply Chain and Logistics, Theoretical Computer Science

      4.7

      (2.9k reseñas)

      Intermediate · Specialization · 3+ Months

    • University of Alberta

      University of Alberta

      Fundamentals of Reinforcement Learning

      Habilidades que obtendrás: Mathematics, Research and Design, Strategy and Operations, Process, Reinforcement Learning, Operations Research, Machine Learning, Reinforcement

      4.8

      (2.3k reseñas)

      Intermediate · Course · 1-3 Months

    • New York University

      New York University

      Machine Learning and Reinforcement Learning in Finance

      Habilidades que obtendrás: Applied Mathematics, Calculus, Computer Programming, Finance, General Statistics, Investment Management, Machine Learning, Machine Learning Algorithms, Markov Model, Mathematics, Probability & Statistics, Python Programming, Reinforcement Learning, Statistical Programming, Theoretical Computer Science

      3.7

      (741 reseñas)

      Intermediate · Specialization · 3+ Months

    • Google Cloud

      Google Cloud

      Machine Learning for Trading

      Habilidades que obtendrás: Accounting, Artificial Neural Networks, Business Analysis, Cloud Computing, Computer Programming, Data Analysis, Finance, Financial Analysis, General Statistics, Investment Management, Machine Learning, Mathematics, Probability & Statistics, Python Programming, Reinforcement Learning, Statistical Programming, Trading

      3.9

      (932 reseñas)

      Intermediate · Specialization · 1-3 Months

    • IBM

      IBM

      Deep Learning and Reinforcement Learning

      Habilidades que obtendrás: Statistical Programming, Python Programming, Computer Programming, Artificial Neural Networks, Deep Learning, Reinforcement Learning, Computer Vision, Machine Learning

      4.6

      (95 reseñas)

      Intermediate · Course · 1-3 Months

    • DeepLearning.AI

      DeepLearning.AI

      Deep Learning

      Habilidades que obtendrás: Algorithms, Applied Machine Learning, Artificial Neural Networks, Bayesian Statistics, Big Data, Communication, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Convolutional Neural Network, Data Management, Deep Learning, Entrepreneurship, General Statistics, Human Computer Interaction, Interactive Design, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematical Optimization, Mathematical Theory & Analysis, Mathematics, Natural Language Processing, Probability & Statistics, Python Programming, Regression, Statistical Machine Learning, Statistical Programming, Strategy and Operations, Theoretical Computer Science

      4.8

      (132.5k reseñas)

      Intermediate · Specialization · 3+ Months

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      New York University

      New York University

      Reinforcement Learning in Finance

      Habilidades que obtendrás: Machine Learning

      3.6

      (118 reseñas)

      Advanced · Course · 1-4 Weeks

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      Google Cloud

      Google Cloud

      Reinforcement Learning: Qwik Start

      Beginner · Project · Less Than 2 Hours

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      Gratis

      University of Washington

      University of Washington

      Computational Neuroscience

      Habilidades que obtendrás: Modeling, Data Analysis, Statistical Programming, Neuroscience, Probability & Statistics, Python Programming, Computer Programming, Marketing, Linear Algebra, Mathematics, Artificial Neural Networks, Reinforcement Learning, Communication, Other Programming Languages, Machine Learning Algorithms, Deep Learning, Data Analysis Software, Machine Learning

      4.6

      (928 reseñas)

      Beginner · Course · 1-3 Months

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      University of Pennsylvania

      University of Pennsylvania

      AI For Business

      Habilidades que obtendrás: Applied Machine Learning, Big Data, Computational Thinking, Computer Programming, Customer Relationship Management, Customer Success, Data Management, Database Administration, Databases, Entrepreneurship, Finance, Human Resources, Leadership and Management, Machine Learning, Marketing, People Management, Reinforcement Learning, Sales, Security Engineering, Software Security, Strategy and Operations, Theoretical Computer Science

      4.6

      (69 reseñas)

      Beginner · Specialization · 3+ Months

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      University of Alberta

      University of Alberta

      A Complete Reinforcement Learning System (Capstone)

      Habilidades que obtendrás: Artificial Neural Networks, Reinforcement Learning, Machine Learning, Reinforcement

      4.7

      (550 reseñas)

      Intermediate · Course · 1-3 Months

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      Gratis

      Caltech

      Caltech

      The Science of the Solar System

      Habilidades que obtendrás: Entrepreneurship, Data Analysis, Business Analysis, Human Learning, Critical Thinking, Problem Solving, Design and Product, Geology, Leadership and Management, Mathematics, Exploratory Data Analysis, Mathematical Theory & Analysis, Data Visualization, Business Psychology, Scientific Visualization, Research and Design, Probability & Statistics, Strategy and Operations, Reinforcement Learning, Product Lifecycle, Machine Learning

      4.8

      (689 reseñas)

      Mixed · Course · 1-3 Months

    Búsquedas relacionadas con reinforcement learning

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    En síntesis, estos son los 10 cursos más populares reinforcement learning

    • Reinforcement Learning: University of Alberta
    • Fundamentals of Reinforcement Learning: University of Alberta
    • Machine Learning and Reinforcement Learning in Finance: New York University
    • Machine Learning for Trading: Google Cloud
    • Deep Learning and Reinforcement Learning: IBM
    • Deep Learning: DeepLearning.AI
    • Reinforcement Learning in Finance: New York University
    • Reinforcement Learning: Qwik Start: Google Cloud
    • Computational Neuroscience: University of Washington
    • AI For Business: University of Pennsylvania

    Habilidades que puedes aprender en Machine Learning

    Programación Python (33)
    TensorFlow (32)
    Aprendizaje Profundo (30)
    Red Neuronal Artificial (24)
    Macrodatos (18)
    Clasificación Estadística (17)
    Álgebra (10)
    Bayesiana (10)
    Álgebra Lineal (10)
    Regresión Lineal (9)
    NumPy (9)

    Preguntas frecuentes sobre Aprendizaje por refuerzo

    • Reinforcement learning is a machine learning paradigm in which software agents use a process of trial and error to learn how to complete tasks in a way that maximizes cumulative rewards as defined by their programmers. In contrast to supervised learning paradigms, reinforcement learning systems do not need labeled input/output pairs or explicit corrections of suboptimal actions; and, in contrast to unsupervised learning, reinforcement learning defines an explicit goal, which is the maximization of the value returned by the Q-learning (or “quality” learning) algorithm as a result of its actions.

      Because it combines the goal orientation of supervised learning with the flexibility of unsupervised learning, reinforcement learning is very important in creating artificial intelligence (AI) applications requiring successful problem-solving in complex situations. For example, they are often used in financial engineering to develop optimal trading algorithms for the stock market. They are also used to build intelligent systems to allow robots and self-driving cars to navigate real-world environments safely.‎

    • As one of the main paradigms for machine learning, reinforcement learning is an essential skill for careers in this fast-growing field. Reinforcement learning is particularly important for developing artificially intelligent digital agents for real-world problem-solving in industries like finance, automotive, robotics, logistics, and smart assistants. According to Glassdoor, the average annual salary for machine learning engineers in America is $114,121 per year, a high level of pay which reflects the high level of demand for this expertise.‎

    • Absolutely. Coursera hosts a wide variety of courses in reinforcement learning and related topics in machine learning, as well as the use of these techniques in applied contexts such as finance and self-driving cars. These courses and Specializations are offered by top-ranked institutions in this field, including the deepmind.ai, New York University, the University of Toronto, and the University of Alberta’s Machine Intelligence Institute. You can learn remotely on a flexible schedule while still getting feedback from expert professors and instructors, ensuring that you’ll get a high quality education with all the reinforcement you need to learn these valuable skills with confidence.‎

    • Because reinforcement learning itself isn't a beginner-level subject, you'll need to have a good grasp on the fundamentals of machine learning before starting to learn it. Additionally, many courses will require you to have a strong background in high-level mathematics such as linear algebra, statistics, and probability. Most courses will require you to be proficient in Python, although people familiar with other programming languages like C++, Matlab, and JavaScript can often use those skills to help them learn reinforcement learning. Having the ability to implement algorithms from pseudocode may be another prerequisite. As you progress, you'll gain skills in using reinforcement learning solutions to solve problems with probabilistic artificial intelligence, function approximation, and intelligent systems.‎

    • People best suited to roles within the reinforcement learning realm should have a passion for machine learning with a drive for analytics and data and an interest in providing frontline support to solve real-world problems while leveraging innate creative problem-solving skills. Additionally, many companies like to see that candidates have strong communication skills and the ability to collaborate across disciplines and departments. There are a variety of roles associated with reinforcement learning, including analysts, engineers, and researchers. In late February 2021, there were more than 1,800 job listings for people proficient in reinforcement learning on LinkedIn.‎

    • If you want to be a part of the future of machine learning, learning reinforcement learning may be a good move for you. This innovative machine learning technique creates an algorithm that learns through trial and error, leading to a combination of short- and long-term rewards such as the ability to define sequences to solve problems using a reward-based learning approach. It's useful across multiple industries, including the tech industry, business, advertising, finance, and e-commerce, all of which find reinforcement learning useful in part because of its ability to offer greater personalization. Ultimately, if you want to work within AI and machine learning, this could be a step to advancing your goals.‎

    Se puso a disposición este contenido de preguntas frecuentes solo con fines informativos. Se les pide a los estudiantes que realicen investigaciones adicionales para asegurarse de que los cursos y otras credenciales cumplan con sus objetivos personales, profesionales y financieros.
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