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    Results for "deep learning"

    • DeepLearning.AI

      Calculus for Machine Learning and Data Science

      Skills you'll gain: Applied Mathematics, Calculus, NumPy, Machine Learning, Jupyter, Python Programming, Artificial Neural Networks, Visualization (Computer Graphics), Deep Learning, Derivatives

      4.8
      Rating, 4.8 out of 5 stars
      ·
      823 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Coursera Project Network

      Curso Completo de Deep Learning

      Skills you'll gain: Keras (Neural Network Library), Deep Learning, Applied Machine Learning, Artificial Neural Networks, Machine Learning, Data Processing

      Intermediate · Guided Project · Less Than 2 Hours

    • DeepLearning.AI

      Custom Models, Layers, and Loss Functions with TensorFlow

      Skills you'll gain: Tensorflow, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Network Model, Network Architecture, Machine Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.1K reviews

      Intermediate · Course · 1 - 3 Months

    • DeepLearning.AI

      Advanced Computer Vision with TensorFlow

      Skills you'll gain: Computer Vision, Tensorflow, Image Analysis, Applied Machine Learning, Deep Learning, Artificial Neural Networks, Visualization (Computer Graphics), Machine Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      518 reviews

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      AI for Medical Diagnosis

      Skills you'll gain: Image Analysis, Predictive Modeling, Risk Modeling, Data Processing, Artificial Intelligence, Classification And Regression Tree (CART), Applied Machine Learning, Computer Vision, Deep Learning, Natural Language Processing, Machine Learning, Radiology, Artificial Neural Networks, Probability & Statistics, Supervised Learning

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

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Apply Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Data Ethics, Computer Vision, Deep Learning, Applied Machine Learning, Machine Learning, Data Transformation, Information Privacy, Data Synthesis

      4.8
      Rating, 4.8 out of 5 stars
      ·
      543 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Placeholder

      DeepLearning.AI

      Supervised Machine Learning: Regression and Classification

      Skills you'll gain: Supervised Learning, Jupyter, Artificial Intelligence and Machine Learning (AI/ML), Scikit Learn (Machine Learning Library), Machine Learning, NumPy, Machine Learning Algorithms, Predictive Modeling, Feature Engineering, Artificial Intelligence, Classification And Regression Tree (CART), Python Programming, Regression Analysis, Unsupervised Learning, Statistical Modeling, Data-Driven Decision-Making, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      28K reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder

      Simplilearn

      AI ML with Deep Learning and Supervised Models

      Skills you'll gain: Supervised Learning, Data Modeling, Applied Machine Learning, Data Analysis, Machine Learning Algorithms, Regression Analysis, Unsupervised Learning, Artificial Intelligence, Classification And Regression Tree (CART), Tensorflow, Deep Learning, Data Science, Keras (Neural Network Library), Machine Learning, Predictive Modeling, Data Mining, Artificial Neural Networks, Predictive Analytics, Artificial Intelligence and Machine Learning (AI/ML), Data Ethics

      Beginner · Specialization · 1 - 3 Months

    • Placeholder

      Packt

      Deep Learning with Keras and Practical Applications

      Skills you'll gain: Keras (Neural Network Library), Image Analysis, Exploratory Data Analysis, Deep Learning, Data Processing, Artificial Neural Networks, Tensorflow, Computer Vision, Machine Learning Methods, Applied Machine Learning, Google Cloud Platform, Classification And Regression Tree (CART), Data Visualization Software

      Intermediate · Course · 3 - 6 Months

    • Placeholder

      Packt

      Deep Learning - Artificial Neural Networks with TensorFlow

      Skills you'll gain: Tensorflow, Artificial Neural Networks, Applied Machine Learning, Deep Learning, Keras (Neural Network Library), Image Analysis, Classification And Regression Tree (CART), Supervised Learning, Machine Learning, Regression Analysis

      Intermediate · Course · 1 - 3 Months

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      MathWorks

      Advanced Deep Learning Techniques for Computer Vision

      Skills you'll gain: Anomaly Detection, Image Analysis, Computer Vision, Matlab, Deep Learning, Applied Machine Learning, Application Deployment, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Data Synthesis, Data Manipulation

      4.9
      Rating, 4.9 out of 5 stars
      ·
      9 reviews

      Beginner · Course · 1 - 4 Weeks

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      DeepLearning.AI

      Réseaux neuronaux et Deep Learning

      Skills you'll gain: Deep Learning, Supervised Learning, Artificial Neural Networks, Artificial Intelligence, Machine Learning, Performance Tuning, Network Architecture, Python Programming, NumPy, Linear Algebra

      4.9
      Rating, 4.9 out of 5 stars
      ·
      18 reviews

      Intermediate · Course · 1 - 4 Weeks

    Searches related to deep learning

    deep learning specialization
    deep learning ai
    deep learning.ai
    deep learning frameworks and neural networks simplified
    deep learning and reinforcement learning
    deep learning with pytorch
    deep learning with keras and tensorflow
    deep learning with pytorch : image segmentation
    1…789…421

    In summary, here are 10 of our most popular deep learning courses

    • Calculus for Machine Learning and Data Science: DeepLearning.AI
    • Curso Completo de Deep Learning: Coursera Project Network
    • Custom Models, Layers, and Loss Functions with TensorFlow: DeepLearning.AI
    • Advanced Computer Vision with TensorFlow: DeepLearning.AI
    • AI for Medical Diagnosis: DeepLearning.AI
    • Apply Generative Adversarial Networks (GANs): DeepLearning.AI
    • Supervised Machine Learning: Regression and Classification : DeepLearning.AI
    • AI ML with Deep Learning and Supervised Models: Simplilearn
    • Deep Learning with Keras and Practical Applications: Packt
    • Deep Learning - Artificial Neural Networks with TensorFlow: Packt

    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 Deep Learning

    Deep learning is a powerful application of machine learning (ML) algorithms modeled after biological systems of information processing called artificial neural networks (ANN). Machine learning is an artificial intelligence (AI) technique that allows computers to automatically learn from data without explicit programming, and deep learning harnesses multiple layers of interconnected neural networks to generate more sophisticated insights.

    While this field of computer science is quite new, it is already being used in a growing range of important applications. Deep learning excels at automated image recognition, also known as computer vision, which is used for creating accurate facial recognition systems and safely driving autonomous vehicles. This approach is also used for speech recognition and natural language processing (NLP) applications, which allow for computers to interact with human users via voice commands.

    Machine learning algorithms such as logistic regression are key to creating deep learning applications, along with commonly used programming languages such as Tensorflow and Python. These programming languages are generally preferred for teaching and learning in this field due to their flexibility and relative accessibility - an important priority given the relevance of deep learning to a wide range of professionals without a computer science background.‎

    A familiarity with the capabilities and development process for deep learning applications can be an asset in a growing number of careers. For example, the use of deep learning is being explored in healthcare for automatic reading of radiology images, as well as searching for patterns in genes and pharmaceutical interactions that can aid in the discovery of new types of medicines. In many fields, even a basic understanding of deep learning can help professionals identify new potential applications of this powerful technology.

    Those with a deeper expertise in deep learning may become computer research scientists in this field, responsible for inventing new algorithms and finding new applications for these techniques. Given the wide range of uses for deep learning, computer scientists in this field are in high demand for jobs at private companies as well as government agencies and research universities. According to the Bureau of Labor Statistics, computer research scientists earned a median annual salary of $122,840 as of 2019, and these jobs are expected to grow much faster than average.‎

    Certainly - in fact, Coursera is one of the best places to learn about deep learning. Through partnerships with deeplearning.ai and Stanford University, Coursera offers courses as well as Specializations taught by some of the pioneering thinkers and educators in this field. You can also learn via courses and Specializations from industry leaders such as Google Cloud and Intel, or get a professional certificate from IBM. Guided Projects also offer an opportunity to build skills in deep learning through hands-on tutorials led by experienced instructors, allowing you to learn with confidence.‎

    The skills or experience you may need to have before studying deep learning, and which can help you better understand an advanced concept such as deep learning, can include sign language reading, music generation, and natural language processing (NLP), in addition to many others. If you have knowledge of Python 3 and understand the basic concepts of general machine-learning algorithms and deep learning, you may have the necessary skills to learn this specialization. You may also want to know about probability and statistics to study deep learning concepts. Basic math, such as algebra and calculus, is also an important prerequisite to deep learning because it relates to machine learning and data science. Also, if you have worked in the tech or artificial intelligence (AI) fields, you may have the necessary experience to study deep learning.‎

    The type of person who is best suited to study deep learning is someone comfortable working with statistics, programming, advanced calculus, advanced algebra, and engineering. Deep learning benefits someone passionate about working in the AI fields which can create types of deep learning networks that help machines perform human functions. A person best suited to learn about deep learning has a vested interest in understanding how the intelligence is built to run everything from driverless cars, mobile devices, stock trading systems, and robotic surgery equipment, for example. Deep learning benefits someone with a goal of working with systems such as computer vision, speech recognition, NLP, audio recognition bioinformatics systems, and medical image analysis.‎

    Deep learning may be right for you if you want to break into AI. The specialization may benefit you if you are a machine learning researcher or practitioner who is seeking to learn the next generation of machine learning, and you want to develop practical skills in the popular deep learning framework TensorFlow. Deep learning is one of the most highly sought-after skills in tech, and mastering it may lead you to many opportunities in the field of AI. It may also benefit you if you want to learn how to build neural networks and how to lead successful machine learning projects, and if you have a passion for learning about convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and how to master concepts in Python and TensorFlow.‎

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

    Yes, Coursera offers a variety of free courses across many topics, including deep learning. While you can access most course materials for free by auditing the courses, this does not include graded assignments or a completion certificate. For those looking to obtain a certificate to showcase their learning or enhance their professional profile, Coursera provides the option to purchase the course. Additionally, Coursera offers free trials or financial aid to learners who qualify, making certifications more accessible to everyone.‎

    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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