Deeplearning.ai Announcing New 5 Deep Learning Courses on Coursera

Deeplearning.ai: Announcing New Deep Learning Courses on Coursera

Deeplearning.ai: Announcing New 5 Deep Learning Courses on Coursera

 

Step by step instructions to Master Deep Learning, and Break into AI.

In the event that you need to break into AI, this Specialization will enable you to do as such. Deep Learning is a standout amongst the most very looked for after abilities in tech. This course will enable you to wind up plainly great at Deep Learning.

In five courses listed underneath, you will learn the foundations of Deep Learning, see how to build neural systems, and figure out how to lead successful machine learning projects. You will find out about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier initialization, and then some.

You will chip away at case studies from medicinal services, autonomous driving, sign language reading, music generation, and natural language processing. You will ace the theory, as well as perceive how it is connected in industry. You will rehearse every one of these thoughts in Python and in TensorFlow, which we will educate.

AI is transforming multiple industries. In the wake of completing this specialization, you will probably discover inventive approaches to apply it to your work.

 

COURSE 1 : Neural Networks and Deep Learning

 

Neural Networks and Deep Learning

 

 

Course Link : Click Here

 

 

About the Course

On the off chance that you need to break into cutting-edge AI, this course will enable you to do as such. Deep learning engineers are exceptionally looked for after, and acing Deep learning will give you various new vocation openings. Deep learning is additionally another “superpower” that will give you a chance to build AI frameworks that simply weren’t conceivable a couple of years back.

In this course, you will take in the foundations of Deep learning. When you complete this class, you will: – Understand the major technology trends driving Deep Learning – Have the capacity to construct, prepare and apply completely associated Deep neural systems.

This course likewise shows you how Deep Learning really functions, as opposed to cursory or surface-level description. So in the wake of finishing it, you will have the capacity to apply Deep Learning out how to a your own particular applications. In the event that you are searching for an job in AI, after this course you will likewise have the capacity to answer fundamental interview questions.

 

COURSE 2 : Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

 

Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization

 

Course Link : Click Here 


 

About the Course

This course will show you the “magic” of getting deep learning out how to function well. Instead of the Deep learning process being a discovery, you will understand what drives execution, and have the capacity to all the more deliberately get great outcomes. You will likewise learn TensorFlow.

In this course you will: – Comprehend industry best-hones for building Deep learning applications. – Have the capacity to successfully utilize the basic neural system “traps”, including instatement, L2 and dropout regularization, Group standardization, inclination checking.

 

 

COURSE 3 : Structuring Machine Learning Projects 

 

Structuring Machine Learning Projects

 

Course Link : Click Here 

 

About the Course

You will figure out how to build an effective machine learning project. On the off chance that you try to be a specialized pioneer in AI, and know how to set bearing for your collaboration, this course will demonstrate to you how. A lot of this substance has never been instructed somewhere else, and is drawn from experience building and dispatching numerous Deep learning products.

This course additionally has two “flight simulators” that let you rehearse basic leadership as a machine learning project leader. This gives “industry encounter” that you may some way or another get simply following quite a while of ML work involvement.

In this course you will: – See how to analyze mistakes in a machine learning framework, and – Have the capacity to organize the most encouraging headings for lessening blunder – Comprehend complex ML settings, for example, bungled preparing/test sets, and contrasting with as well as outperforming human-level execution.

 

 

COURSE 4 : Convolutional Neural Networks

 

Convolutional Neural Networks

 

Course Link : Click Here

 

About the Course

This course will show you how to construct convolutional neural systems and apply it to image data. On account of Deep learning, computer vision is working obviously better than only two years back, and this is empowering various exciting applications going from safe self-ruling driving, to accurate face recognition, to automatic reading of radiology images.

In this course You will: – See how to construct a convolutional neural system, including recent variations such as residual networks. – Know how to apply convolutional systems to visual identification and acknowledgment undertakings. – Know to utilize neural style transfer to generate art. – Have the capacity to apply these algorithms to a variety of image, video, and other 2D or 3D data.

 

COURSE 5 : Sequence Models

 

Sequence Models

 

Course Link : Click Here

 

About the Course

This course will show you how to build models for natural language, audio, and other sequence data. On account of Deep learning, sequence algorithms are working much better than only two years prior, and this is empowering various energizing applications in speech recognition, music synthesis, chatbots, machine translation, natural language understanding, and many others.

You will: – See how to build and train Recurrent Neural Networks (RNNs), and commonly-used variants such as GRUs and LSTMs. – Be able to apply sequence models to natural language problems, including text synthesis. Have the capacity to apply sequence models to audio applications, including speech recognition and msynthesis.


 

Educators:

Andrew Ng

Co-founder, Coursera; Adjunct Professor, Stanford University; formerly head of Baidu AI Group/Google Brain

 

Teaching Assistant – Younes Bensouda Mourri

Mathematical & Computational Sciences, Stanford University

 

Teaching Assistant – Kian Katanforoosh

M.S. Stanford University (Walter J. Gores 2017), B.S Ecole Centrale Paris

 

Details on the course can be found here.

 

Note: When these courses become available for free in future will update here.

 

 

 

Related:

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