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TensorFlow 2 for Deep Learning Specialization Imperial College London Hooray! Now I completed the whole specialization! TensorFlow skill...

Probabilistic Deep Learning with TensorFlow 2Imperial College London The focus of this course is the TensorFlow Probability library....

The Variational Autoencoder (VAE) is an algorithm for inference and learning in a latent variable generative model. In...

Generative models are a kind of statistical model that aims to learn the underlying data distribution itself. If a generative...

Unfortunately, deep learning models aren’t always accurate, especially when asked to make predictions on new data points that are dissimilar to the...

We’ll be making extensive use of the TensorFlow Probability library to help us develop probabilistic deep learning models. The...

Customising Your Models with TensorFlow 2Imperial College London I highly recommend this course to everyone who is willing...

Subclassing Models The model subclassing and custom layers give you even more control over how the model is...

Sequential data is data that has a natural sequential structure built into it, like text data or audio...

Data pipelines are for loading, transforming, and filtering a wide range of different data for use in your...

The reason you might want to use the Functional API (instead of the Sequential API) is if you...

Getting started with TensorFlow 2Imperial College London Wow this is a wonderful course on Tensorflow! The professor and...

Introduction to TensorFlowGoogle Quite a lot stuff of TensorFlow was distilled into this course, from the basics to...

TensorFlow is an open-source, high-performance library for any numerical computation (not just for machine learning). For example, you...

Andrew Ng Anna Koop Brenda Gunderson Computer Communications Specialization Cryptography Differential Equations for Engineers Economics of Money and Banking Evgenii Vashukevich Foundations of Quantum Mechanics Garud Iyengar Ivan Vybornyi Jeffrey Chasnov John Daily Jonathan Katz Kevin Webster Ling-Chieh Kung Machine Learning: Algorithms in the Real World Martin Haugh Mathematics for Engineers Specialization Matthew Hutchens Michael Donohoe Michael Fricke Microsoft Azure Fundamentals AZ-900 Exam Prep Specialization Operations Research (3): Theory Perry Mehrling Petro Lisowsky Physical Basics of Quantum Computing Practical Reinforcement Learning Rebekah May Search Engine Optimization (SEO) Specialization Sergey Sysoev Statistical Thermodynamics Specialization Statistics with Python Specialization Taxation of Business Entities I: Corporations TensorFlow 2 for Deep Learning Specialization U.S. Federal Taxation Specialization Understanding Modern Physics I: Relativity and Cosmology Wounjhang Park Xiaobo Zhou Yi Wang

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