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    • Neural Networks

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    350 results for "neural networks"

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      DeepLearning.AI

      Deep Learning

      Skills you'll gain: Advertising, Algorithms, 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, Decision Making, 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, Modeling, Natural Language, Natural Language Processing, Network Architecture, Network Model, Probability & Statistics, Project, Project Management, Python Programming, Regression, Sales, Speech, 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

      (134.2k reviews)

      Intermediate · Specialization · 3-6 Months

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      DeepLearning.AI

      Neural Networks and Deep Learning

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

      4.9

      (114.8k reviews)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI, Stanford University

      Machine Learning

      Skills you'll gain: 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

      (2.2k reviews)

      Beginner · Specialization · 1-3 Months

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      IBM Skills Network

      Advanced Data Science with IBM

      Skills you'll gain: Algorithms, Apache, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Bayesian Statistics, Big Data, Change Management, Cloud Computing, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Model, Data Structures, Data Visualization, Databases, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, Extract, Transform, Load, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Natural Language Processing, Plot (Graphics), Probability & Statistics, Probability Distribution, Programming Principles, Python Programming, Regression, SQL, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Tensorflow, Theoretical Computer Science

      4.3

      (2.9k reviews)

      Advanced · Specialization · 3-6 Months

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      IBM Skills Network

      Introduction to Deep Learning & Neural Networks with Keras

      Skills you'll gain: Computer Programming, Deep Learning, Theoretical Computer Science, Artificial Neural Networks, Python Programming, Keras, Probability & Statistics, Statistical Programming, Machine Learning, Algorithms, Mathematics, Convolutional Neural Network

      4.7

      (1.1k reviews)

      Intermediate · Course · 1-3 Months

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      DeepLearning.AI

      AI For Everyone

      Skills you'll gain: Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Ethics, Machine Learning

      4.8

      (36.3k reviews)

      Beginner · Course · 1-4 Weeks

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      Johns Hopkins University

      Advanced Statistics for Data Science

      Skills you'll gain: Algebra, Artificial Neural Networks, Bayesian Statistics, Biostatistics, Calculus, Communication, Dimensionality Reduction, Econometrics, Experiment, General Statistics, Linear Algebra, Machine Learning, Machine Learning Algorithms, Mathematics, Probability & Statistics, Probability Distribution, Regression, Statistical Machine Learning, Statistical Tests

      4.4

      (660 reviews)

      Advanced · Specialization · 3-6 Months

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      DeepLearning.AI

      DeepLearning.AI TensorFlow Developer

      Skills you'll gain: 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 Processing, Probability & Statistics, Programming Principles, Python Programming, Statistical Classification, Statistical Machine Learning, Statistical Programming, Tensorflow, Time Series

      4.7

      (22.2k reviews)

      Intermediate · Professional Certificate · 3-6 Months

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      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Python Programming, Keras, Computer Networking, Computer Programming, Applied Machine Learning, Deep Learning, Computer Graphics, Artificial Neural Networks, Statistical Programming, Computer Vision, Object Detection, Tensorflow, Network Architecture, Machine Learning, Convolutional Neural Network, Computer Architecture, Computer Graphic Techniques

      4.9

      (40.6k reviews)

      Intermediate · Course · 1-4 Weeks

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      University of Colorado Boulder

      Deep Learning Applications for Computer Vision

      Skills you'll gain: Deep Learning, Computer Vision, Machine Learning

      4.7

      (30 reviews)

      Intermediate · Course · 1-3 Months

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      DeepLearning.AI

      Convolutional Neural Networks in TensorFlow

      Skills you'll gain: Computer Programming, Deep Learning, Statistical Machine Learning, Artificial Neural Networks, Entrepreneurship, Python Programming, Computer Vision, Statistical Programming, Machine Learning Algorithms, Convolutional Neural Network, Tensorflow, Computer Graphic Techniques, Machine Learning, Statistical Classification, Applied Machine Learning, Computer Graphics, Keras

      4.7

      (7.4k reviews)

      Intermediate · Course · 1-4 Weeks

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      Coursera Project Network

      Hyperparameter Tuning with Neural Network Intelligence

      Skills you'll gain: Artificial Neural Networks, Choice, Machine Learning

      4.7

      (37 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

    Searches related to neural networks

    neural networks and deep learning
    neural networks and random forests
    convolutional neural networks
    convolutional neural networks in tensorflow
    deep neural networks with pytorch
    improving deep neural networks: hyperparameter tuning, regularization and optimization
    introduction to deep learning & neural networks with keras
    predicting the weather with artificial neural networks
    1234…30

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

    • Deep Learning: DeepLearning.AI
    • Neural Networks and Deep Learning: DeepLearning.AI
    • Machine Learning: DeepLearning.AI
    • Advanced Data Science with IBM: IBM Skills Network
    • Introduction to Deep Learning & Neural Networks with Keras: IBM Skills Network
    • AI For Everyone: DeepLearning.AI
    • Advanced Statistics for Data Science: Johns Hopkins University
    • DeepLearning.AI TensorFlow Developer: DeepLearning.AI
    • Convolutional Neural Networks: DeepLearning.AI
    • Deep Learning Applications for Computer Vision: University of Colorado Boulder

    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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