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    • Neural Networks

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    506 results for "neural networks"

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      University of Washington

      Computational Neuroscience

      Skills you'll gain: Data Science, Machine Learning, Artificial Neural Networks, Python Programming, Statistical Programming, Matlab, Reinforcement Learning, Business Psychology, Communication, Computer Networking, Computer Programming, Data Analysis, Data Analysis Software, Deep Learning, Entrepreneurship, General Statistics, Linear Algebra, Machine Learning Algorithms, Mathematics, Network Model, Probability & Statistics, Probability Distribution

      4.6

      (1k reviews)

      Beginner · Course · 1-3 Months

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      DeepLearning.AI

      Advanced Learning Algorithms

      Skills you'll gain: Machine Learning, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Applied Machine Learning, Computer Programming, Python Programming, Statistical Programming, Theoretical Computer Science, Tensorflow, Algorithms, Data Management, Data Structures, Probability & Statistics, General Statistics, Statistical Machine Learning, Computer Vision, Mathematics, Probability Distribution, Computational Logic, Linear Algebra, Mathematical Theory & Analysis

      4.9

      (1.9k reviews)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      Calculus for Machine Learning and Data Science

      Skills you'll gain: Algorithms, Calculus, Mathematics, Theoretical Computer Science, Machine Learning, Mathematical Theory & Analysis, Machine Learning Algorithms, Artificial Neural Networks, Deep Learning, Differential Equations, Probability & Statistics, Regression, Statistical Machine Learning, Algebra, Econometrics, General Statistics, Python Programming

      4.8

      (59 reviews)

      Beginner · Course · 1-4 Weeks

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      DeepLearning.AI

      Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

      Skills you'll gain: Deep Learning, Machine Learning, Probability & Statistics, Statistical Machine Learning, Statistical Programming, Artificial Neural Networks, Machine Learning Algorithms, Python Programming, General Statistics, Linear Algebra, Applied Machine Learning, Applied Mathematics, Dimensionality Reduction, Feature Engineering, Machine Learning Software, Mathematical Theory & Analysis, Mathematics, Statistical Visualization, Computer Programming, Tensorflow, Algorithms, Calculus, Probability Distribution, Regression, Theoretical Computer Science

      4.9

      (61.9k reviews)

      Intermediate · Course · 1-4 Weeks

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      DeepLearning.AI

      Convolutional Neural Networks in TensorFlow

      Skills you'll gain: Machine Learning, Artificial Neural Networks, Deep Learning, Tensorflow, Computer Vision, Business Psychology, Computer Programming, Data Science, Entrepreneurship, General Statistics, Probability & Statistics, Python Programming, Statistical Programming, Applied Machine Learning, Calculus, Machine Learning Algorithms, Mathematics, Computer Graphic Techniques, Computer Graphics, Statistical Machine Learning

      4.7

      (7.7k reviews)

      Intermediate · Course · 1-4 Weeks

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      IBM Skills Network

      Deep Neural Networks with PyTorch

      Skills you'll gain: Machine Learning, Computer Programming, Python Programming, Computer Vision, Deep Learning, Probability & Statistics, Artificial Neural Networks, Regression, General Statistics, Machine Learning Algorithms, Algorithms, Theoretical Computer Science, Econometrics, Computer Graphic Techniques, Computer Graphics, Machine Learning Software, Probability Distribution, Statistical Machine Learning

      4.4

      (1.3k reviews)

      Intermediate · Course · 1-3 Months

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      Coursera Project Network

      Predicting the Weather with Artificial Neural Networks

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

      3.8

      (11 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Machine Learning: Predict Numbers from Handwritten Digits using a Neural Network, Keras, and R

      Skills you'll gain: Computer Programming, Machine Learning, Statistical Programming

      4.4

      (71 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Simple Recurrent Neural Network with Keras

      Skills you'll gain: Artificial Neural Networks, Machine Learning, Natural Language Processing, Data Science, Tensorflow

      4.5

      (118 reviews)

      Intermediate · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      بناء Neural Network مكونه من 3 طبقات بأستخدام لغة Python

      Skills you'll gain: Python Programming

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Diabetes Disease Detection with XG-Boost and Neural Networks

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

      Beginner · Guided Project · Less Than 2 Hours

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      Coursera Project Network

      Hyperparameter Tuning with Neural Network Intelligence

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

      4.7

      (38 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
    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
    1234…43

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

    • Computational Neuroscience: University of Washington
    • Advanced Learning Algorithms: DeepLearning.AI
    • Calculus for Machine Learning and Data Science: DeepLearning.AI
    • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization: DeepLearning.AI
    • Convolutional Neural Networks in TensorFlow: DeepLearning.AI
    • Deep Neural Networks with PyTorch: IBM Skills Network
    • Predicting the Weather with Artificial Neural Networks: Coursera Project Network
    • Machine Learning: Predict Numbers from Handwritten Digits using a Neural Network, Keras, and R: Coursera Project Network
    • Simple Recurrent Neural Network with Keras: Coursera Project Network
    • بناء Neural Network مكونه من 3 طبقات بأستخدام لغة Python: Coursera Project Network

    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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