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    Results for "deep learning"

    • University of Colorado Boulder

      Deep Learning Applications for Computer Vision

      Skills you'll gain: Tensorflow, Computer Vision, Image Analysis, PyTorch (Machine Learning Library), Artificial Neural Networks, Applied Machine Learning, Deep Learning, Machine Learning Algorithms, Machine Learning, Artificial Intelligence, Computer Programming Tools, Algorithms

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      87 reviews

      Intermediate · Course · 1 - 3 Months

    • Google Cloud

      Advanced Machine Learning on Google Cloud

      Skills you'll gain: Natural Language Processing, MLOps (Machine Learning Operations), Tensorflow, Large Language Modeling, Reinforcement Learning, Computer Vision, Google Cloud Platform, Keras (Neural Network Library), Systems Design, Image Analysis, Hybrid Cloud Computing, Applied Machine Learning, Systems Architecture, Performance Tuning, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Artificial Neural Networks, Machine Learning, Machine Learning Algorithms, Distributed Computing

      4.5
      Rating, 4.5 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • Google

      The Nuts and Bolts of Machine Learning

      Skills you'll gain: Feature Engineering, Statistical Machine Learning, Advanced Analytics, Predictive Modeling, Unsupervised Learning, Data Ethics, Machine Learning, Machine Learning Algorithms, Supervised Learning, Data Analysis, Performance Tuning, Python Programming

      4.8
      Rating, 4.8 out of 5 stars
      ·
      513 reviews

      Advanced · Course · 1 - 3 Months

    • Duke University

      Introduction to Machine Learning

      Skills you'll gain: PyTorch (Machine Learning Library), Reinforcement Learning, Image Analysis, Applied Machine Learning, Deep Learning, Machine Learning, Natural Language Processing, Supervised Learning, Unsupervised Learning, Artificial Neural Networks, Computer Vision, Medical Imaging

      4.7
      Rating, 4.7 out of 5 stars
      ·
      3.7K reviews

      Intermediate · Course · 1 - 3 Months

    • DeepLearning.AI

      Generative Deep Learning with TensorFlow

      Skills you'll gain: Generative AI, Tensorflow, Image Analysis, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Computer Graphics, Unsupervised Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      306 reviews

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Calculus for Machine Learning and Data Science

      Skills you'll gain: Applied Mathematics, Calculus, Numerical Analysis, Mathematical Modeling, Machine Learning, Python Programming, Regression Analysis, Artificial Neural Networks, Deep Learning, Derivatives

      4.8
      Rating, 4.8 out of 5 stars
      ·
      848 reviews

      Intermediate · Course · 1 - 4 Weeks

    • DeepLearning.AI

      Sequence Models

      Skills you'll gain: Natural Language Processing, Artificial Neural Networks, Tensorflow, Large Language Modeling, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Deep Learning, Applied Machine Learning

      4.8
      Rating, 4.8 out of 5 stars
      ·
      31K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Coursera Project Network

      Sentiment Analysis with Deep Learning using BERT

      Skills you'll gain: Text Mining, PyTorch (Machine Learning Library), Data Processing, Performance Tuning, Deep Learning, Natural Language Processing

      4.4
      Rating, 4.4 out of 5 stars
      ·
      396 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • University of Illinois Urbana-Champaign

      Advanced Deep Learning Methods for Healthcare

      Skills you'll gain: Deep Learning, Generative AI, Applied Machine Learning, Machine Learning Methods, Image Analysis, Graph Theory, Network Analysis, Artificial Neural Networks, Health Informatics, Machine Learning Software, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Predictive Modeling, Natural Language Processing, Data Synthesis, Python Programming

      3.4
      Rating, 3.4 out of 5 stars
      ·
      13 reviews

      Advanced · Course · 1 - 4 Weeks

    • Imperial College London

      Probabilistic Deep Learning with TensorFlow 2

      Skills you'll gain: Generative AI, Tensorflow, Deep Learning, Image Analysis, Bayesian Statistics, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Dimensionality Reduction

      4.7
      Rating, 4.7 out of 5 stars
      ·
      108 reviews

      Advanced · Course · 1 - 3 Months

    • Packt

      Advanced Machine Learning and Deep Learning

      Skills you'll gain: Deep Learning, Shiny (R Package), Applied Machine Learning, Image Analysis, PyTorch (Machine Learning Library), Predictive Modeling, Artificial Neural Networks, Machine Learning Methods, Statistical Machine Learning, Tensorflow, Classification And Regression Tree (CART), Artificial Intelligence and Machine Learning (AI/ML), Regression Analysis, Dimensionality Reduction, Unsupervised Learning, Interactive Data Visualization, Time Series Analysis and Forecasting, Data Processing

      Advanced · Course · 1 - 3 Months

    • DeepLearning.AI

      Advanced Learning Algorithms

      Skills you'll gain: Classification And Regression Tree (CART), Machine Learning Algorithms, Machine Learning, Applied Machine Learning, Data Ethics, Decision Tree Learning, Tensorflow, Artificial Intelligence, Supervised Learning, Deep Learning, Random Forest Algorithm, Artificial Neural Networks, Performance Tuning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      7.8K reviews

      Beginner · Course · 1 - 4 Weeks

    Searches related to deep learning

    deep learning specialization
    deep learning ai
    deep learning: recurrent neural networks with python
    deep learning with pytorch
    deep learning for computer vision
    deep learning with keras and tensorflow
    deep learning with pytorch : generative adversarial network
    deep learning and reinforcement learning
    1…678…435

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

    • Deep Learning Applications for Computer Vision: University of Colorado Boulder
    • Advanced Machine Learning on Google Cloud: Google Cloud
    • The Nuts and Bolts of Machine Learning: Google
    • Introduction to Machine Learning: Duke University
    • Generative Deep Learning with TensorFlow: DeepLearning.AI
    • Calculus for Machine Learning and Data Science: DeepLearning.AI
    • Sequence Models: DeepLearning.AI
    • Sentiment Analysis with Deep Learning using BERT: Coursera Project Network
    • Advanced Deep Learning Methods for Healthcare: University of Illinois Urbana-Champaign
    • Probabilistic Deep Learning with TensorFlow 2: Imperial College London

    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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