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    • Neural Networks

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    507 results for "neural networks"

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      New York University

      Fundamentals of Machine Learning in Finance

      Skills you'll gain: Machine Learning, Markov Model

      3.8

      (321 reviews)

      Intermediate · Course · 1-4 Weeks

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      EIT Digital

      Business Implications of AI: Full course

      Skills you'll gain: Leadership and Management, Machine Learning, Computer Vision, Natural Language Processing

      4.0

      (25 reviews)

      Beginner · Course · 1-4 Weeks

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      University of Colorado Boulder

      Data Mining Methods

      Skills you'll gain: Theoretical Computer Science, Algorithms

      3.0

      (6 reviews)

      Intermediate · Course · 1-4 Weeks

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      Sungkyunkwan University

      Recommender Systems

      Intermediate · Course · 1-4 Weeks

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      L&T EduTech

      Advanced Study of Protection Schemes and Switchgear

      Mixed · Course · 1-3 Months

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      Alberta Machine Intelligence Institute

      Introduction to Applied Machine Learning

      Skills you'll gain: Machine Learning, Applied Machine Learning, Machine Learning Algorithms, Reinforcement Learning

      4.7

      (709 reviews)

      Intermediate · Course · 1-4 Weeks

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      LearnQuest

      Demand Forecasting Using Time Series

      Skills you'll gain: Forecasting, Probability & Statistics, General Statistics, Computer Programming, Correlation And Dependence, Python Programming, Regression, Statistical Programming, Machine Learning

      3.3

      (20 reviews)

      Intermediate · Course · 1-4 Weeks

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      LearnQuest

      Introduction to Data Science and scikit-learn in Python

      Skills you'll gain: Computer Programming, Python Programming, Statistical Programming, Econometrics, General Statistics, Probability & Statistics, Advertising, Communication, Data Science, Machine Learning, Marketing, Regression

      4.0

      (33 reviews)

      Beginner · Course · 1-4 Weeks

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      Free

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      University of Cape Town

      Doing Clinical Research: Biostatistics with the Wolfram Language

      Skills you'll gain: Data Analysis, Probability & Statistics, Operations Research, Strategy and Operations

      4.7

      (47 reviews)

      Beginner · Course · 1-4 Weeks

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      University of Glasgow

      Explainable deep learning models for healthcare - CDSS 3

      Intermediate · Course · 1-4 Weeks

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      Northeastern University

      Engaging in Improving Patient Experience Through Analytics

      Skills you'll gain: Innovation

      Beginner · Course · 1-4 Weeks

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      Free

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      Indian Institute of Technology Roorkee

      Data Mining for Smart Cities

      Skills you'll gain: Machine Learning, Mathematics, Python Programming

      Beginner · Course · 1-3 Months

    Searches related to neural networks

    neural networks and deep learning
    neural networks and random forests
    convolutional neural networks
    deep neural networks with pytorch
    convolutional neural networks in tensorflow
    improving deep neural networks: hyperparameter tuning, regularization and optimization
    introduction to deep learning & neural networks with keras
    predicting the weather with artificial neural networks
    1…40414243

    In summary, here are 10 of our most popular neural networks courses

    • Fundamentals of Machine Learning in Finance: New York University
    • Business Implications of AI: Full course: EIT Digital
    • Data Mining Methods: University of Colorado Boulder
    • Recommender Systems: Sungkyunkwan University
    • Advanced Study of Protection Schemes and Switchgear: L&T EduTech
    • Introduction to Applied Machine Learning: Alberta Machine Intelligence Institute
    • Demand Forecasting Using Time Series: LearnQuest
    • Introduction to Data Science and scikit-learn in Python: LearnQuest
    • Doing Clinical Research: Biostatistics with the Wolfram Language: University of Cape Town
    • Explainable deep learning models for healthcare - CDSS 3: University of Glasgow

    Skills you can learn in Machine Learning

    Python Programming (33)
    Tensorflow (32)
    Deep Learning (30)
    Artificial Neural Network (24)
    Big Data (18)
    Statistical Classification (17)
    Reinforcement Learning (13)
    Algebra (10)
    Bayesian (10)
    Linear Algebra (10)
    Linear Regression (9)
    Numpy (9)

    Frequently Asked Questions about Neural Networks

    • Neural networks, also known as neural nets or artificial neural networks (ANN), are machine learning algorithms organized in networks that mimic the functioning of neurons in the human brain. Using this biological neuron model, these systems are capable of unsupervised learning from massive datasets.

      This is an important enabler for artificial intelligence (AI) applications, which are used across a growing range of tasks including image recognition, natural language processing (NLP), and medical diagnosis. The related field of deep learning also relies on neural networks, typically using a convolutional neural network (CNN) architecture that connects multiple layers of neural networks in order to enable more sophisticated applications.

      For example, using deep learning, a facial recognition system can be created without specifying features such as eye and hair color; instead, the program can simply be fed thousands of images of faces and it will learn what to look for to identify different individuals over time, in much the same way that humans learn. Regardless of the end-use application, neural networks are typically created in TensorFlow and/or with Python programming skills.‎

    • Neural networks are a fundamental concept to understand for jobs in artificial intelligence (AI) and deep learning. And, as the number of industries seeking to leverage these approaches continues to grow, so do career opportunities for professionals with expertise in neural networks. For instance, these skills could lead to jobs in healthcare creating tools to automate X-ray scans or assist in drug discovery, or a job in the automotive industry developing autonomous vehicles.

      Professionals dedicating their careers to cutting-edge work in neural networks typically pursue a master’s degree or even a doctorate in computer science. This high-level expertise in neural networks and artificial intelligence are in high demand; according to the Bureau of Labor Statistics, computer research scientists earn a median annual salary of $122,840 per year, and these jobs are projected to grow much faster than average over the next decade.‎

    • Absolutely - in fact, Coursera is one of the best places to learn about neural networks, online or otherwise. You can take courses and Specializations spanning multiple courses in topics like neural networks, artificial intelligence, and deep learning from pioneers in the field - including deeplearning.ai and Stanford University. Coursera has also partnered with industry leaders such as IBM, Google Cloud, and Amazon Web Services to offer courses that can lead to professional certificates in applied AI and other areas. You can even learn about neural networks with hands-on Guided Projects, a way to learn on Coursera by completing step-by-step tutorials led by experienced instructors.‎

    • Before starting to learn neural networks, it's important to have experience creating and using algorithms since neural networks run on complicated algorithms. You should also have fundamental math skills at least, but you'll be at a better advantage if you have knowledge of linear algebra, calculus, statistics, and probability. Being proficient at problem-solving is also important before starting to learn neural networks. An understanding of how the human brain processes information is helpful since artificial neural networks are patterned after how the brain works. You'll also benefit from having experience using any programming language, in particular Java, R, Python, or C++. This includes experience using these languages' libraries, which you'll access to apply the algorithms used in neural networks.‎

    • People who are best suited for roles in neural networks are innovative, interested in technology, and have the ability to identify patterns in large amounts of data and draw conclusions from them. People who have a desire to make life and work easier for human beings through artificial technology are well suited for roles in neural networks too. Also, people who have good programming skills and data engineering skills like SQL, data analysis, ETL, and data visualization are likely well suited for roles in neural networks.‎

    • If you are interested in the field of artificial intelligence, learning about neural networks is right for you. If your current or future position involves data analysis, pattern recognition, optimization, forecasting, or decision-making, you might also benefit from learning neural networks. Neural networks are also used in image recognition software, speech synthesis, self-driving vehicles, navigation systems, industrial robots, and algorithms for protecting information systems, so if you're interested in these technologies, learning neural networks may be helpful to you.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
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