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    Results for "neural networks"

    • DeepLearning.AI

      Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Data Ethics, Applied Machine Learning, Computer Vision, Machine Learning, Unsupervised Learning, Artificial Intelligence, Information Privacy, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2.3K reviews

      Intermediate · Specialization · 1 - 3 Months

    • DeepLearning.AI

      Apply Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Data Ethics, Computer Vision, Deep Learning, Applied Machine Learning, Machine Learning, Unsupervised Learning, Information Privacy, Artificial Intelligence

      4.8
      Rating, 4.8 out of 5 stars
      ·
      544 reviews

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Build Basic Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Data Ethics, Computer Vision, Artificial Intelligence, Unsupervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Build Better Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Data Ethics, Deep Learning, Machine Learning, Image Analysis, Artificial Neural Networks, Performance Testing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      679 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Rutgers the State University of New Jersey

      Supply Chain Logistics

      Skills you'll gain: Warehouse Management, Inventory and Warehousing, Inventory Management System, Transportation, Supply Chain, and Logistics, Logistics, Transportation Operations, Supply Chain Management, Supply Chain, Customer Service, Operating Cost

      4.8
      Rating, 4.8 out of 5 stars
      ·
      11K reviews

      Beginner · Course · 1 - 4 Weeks

    • Google

      Automate Cybersecurity Tasks with Python

      Skills you'll gain: Debugging, Python Programming, Cybersecurity, Cyber Security Assessment, Scripting, Programming Principles, Algorithms, Automation, Integrated Development Environments, File Management, Data Structures

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Google

      Sound the Alarm: Detection and Response

      Skills you'll gain: Incident Response, Computer Security Incident Management, Intrusion Detection and Prevention, Event Monitoring, Threat Detection, Incident Management, Security Information and Event Management (SIEM), Cybersecurity, Cyber Threat Hunting, Continuous Monitoring, Network Security, Network Monitoring, Document Management, Network Analysis, Splunk, Technical Documentation, TCP/IP, Network Protocols

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3K reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: New
      New

      Simplilearn

      Deep Learning Frameworks and Neural Networks Simplified

      Skills you'll gain: Deep Learning, Tensorflow, Keras (Neural Network Library), Artificial Neural Networks, Artificial Intelligence, Computer Vision, Machine Learning Methods, Data Manipulation

      Beginner · Course · 1 - 4 Weeks

    • Illinois Tech

      Introduction to Contemporary Operating Systems and Hardware 1b

      Skills you'll gain: Networking Hardware, General Networking, Wireless Networks, Network Architecture, Computer Networking, Network Protocols, Local Area Networks, TCP/IP, Network Routers, Network Switches, Wide Area Networks, System Configuration, Servers

      Build toward a degree

      4.5
      Rating, 4.5 out of 5 stars
      ·
      285 reviews

      Beginner · Course · 1 - 4 Weeks

    • Google

      IT Security: Defense against the digital dark arts

      Skills you'll gain: Network Security, Information Systems Security, Cybersecurity, Application Security, Encryption, Security Controls, Cyber Attacks, Security Awareness, Data Security, Cryptography, Threat Modeling, Security Management, Network Administration, Computer Security Awareness Training, Information Assurance, Wireless Networks, Hardening, Firewall, Malware Protection, Authentications

      4.8
      Rating, 4.8 out of 5 stars
      ·
      25K reviews

      Beginner · Course · 1 - 3 Months

    • IBM

      IBM AI Foundations for Business

      Skills you'll gain: Large Language Modeling, Data Literacy, Data Mining, Artificial Intelligence, Generative AI, Data Ethics, Artificial Intelligence and Machine Learning (AI/ML), Big Data, Information Architecture, Strategic Decision-Making, Enterprise Architecture, Cloud Computing, Applied Machine Learning, Data Analysis, Data Science, Deep Learning, Digital Transformation, Data Strategy, Business Strategy, Business Process Automation

      4.7
      Rating, 4.7 out of 5 stars
      ·
      93K reviews

      Beginner · Specialization · 1 - 3 Months

    • Google

      Assets, Threats, and Vulnerabilities

      Skills you'll gain: Threat Modeling, Threat Management, Vulnerability Management, Cyber Threat Intelligence, Cybersecurity, Cyber Attacks, Vulnerability Assessments, Threat Detection, MITRE ATT&CK Framework, Data Security, Cyber Risk, NIST 800-53, Authorization (Computing), Malware Protection, Authentications, Security Strategy, Security Controls, Risk Management Framework, Identity and Access Management, Encryption

      4.8
      Rating, 4.8 out of 5 stars
      ·
      3.6K reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to neural networks

    neural networks and deep learning
    neural networks and random forests
    convolutional neural networks
    artificial neural networks
    introduction to neural networks
    convolutional neural networks in tensorflow
    foundations of neural networks
    introduction to neural networks and pytorch
    1…678…151

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

    • Generative Adversarial Networks (GANs): DeepLearning.AI
    • Apply Generative Adversarial Networks (GANs): DeepLearning.AI
    • Build Basic Generative Adversarial Networks (GANs): DeepLearning.AI
    • Build Better Generative Adversarial Networks (GANs): DeepLearning.AI
    • Supply Chain Logistics: Rutgers the State University of New Jersey
    • Automate Cybersecurity Tasks with Python: Google
    • Sound the Alarm: Detection and Response: Google
    • Deep Learning Frameworks and Neural Networks Simplified: Simplilearn
    • Introduction to Contemporary Operating Systems and Hardware 1b: Illinois Tech
    • IT Security: Defense against the digital dark arts : Google

    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.‎

    Online Neural Networks courses offer a convenient and flexible way to enhance your knowledge or learn new Neural Networks skills. Choose from a wide range of Neural Networks courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Neural Networks, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    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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