Andrew Ng

Andrew Ng is Co-founder of Coursera, and an Adjunct Professor of Computer Science at Stanford University. His machine learning course is the MOOC that had led to the founding of Coursera!

In 2011, he led the development of Stanford University’s main MOOC (Massive Open Online Courses) platform and also taught an online Machine Learning class to over 100,000 students, thus helping launch the MOOC movement and also leading to the founding of Coursera.

Ng also works on machine learning, with an emphasis on deep learning. He had founded and led the “Google Brain” project, which developed massive-scale deep learning algorithms. This resulted in the famous “Google cat” result, in which a massive neural network with 1 billion parameters learned from unlabeled YouTube videos to detect cats. Until recently, he led Baidu's ~1300 person AI Group, which developed technologies in deep learning, speech, computer vision, NLP, and other areas.

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IA para todos (Coursera)

La IA no es solo para ingenieros. Si desea que su organización esté mejor preparada en el uso de la IA, este es el curso que todos deberían hacer, especialmente sus colegas no técnicos.
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Introduction to Machine Learning in Production (Coursera)

Nov 1st 2021
Introduction to Machine Learning in Production (Coursera)
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In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype the [...]
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Nov 1st 2021
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41.00 EUR/month

Sequence Models (Coursera)

This course will teach you how to build models for natural language, audio, and other sequence data. Thanks to deep learning, sequence algorithms are working far better than just two years ago, and this is enabling numerous exciting applications in speech recognition, music synthesis, chatbots, machine translation, natural language [...]
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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (Coursera)

This course will teach you the "magic" of getting deep learning to work well. Rather than the deep learning process being a black box, you will understand what drives performance, and be able to more systematically get good results. You will also learn TensorFlow.
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Structuring Machine Learning Projects (Coursera)

You will learn how to build a successful machine learning project. If you aspire to be a technical leader in AI, and know how to set direction for your team's work, this course will show you how. Much of this content has never been taught elsewhere, and is drawn [...]
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Neural Networks and Deep Learning (Coursera)

If you want to break into cutting-edge AI, this course will help you do so. Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Deep learning is also a new "superpower" that will let you build AI systems that just [...]
6
Average: 6 ( 4 votes )

Convolutional Neural Networks (Coursera)

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to [...]
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Machine Learning (Coursera)

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably [...]
4
Average: 4 ( 3 votes )

IA para todos (Coursera)

IA não é apenas para engenheiros. Se quiser que sua organização se torne melhor no uso de IA, este é o curso que todos, especialmente aos seus colegas não técnicos, devem fazer.
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AI For Everyone (Coursera)

AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take.
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