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Zero to Deep Learning™ with Python and Keras

This course is designed to provide a complete introduction to Deep Learning. It is aimed at beginners and intermediate programmers and data scientists who are familiar with Python and want to understand and apply Deep Learning techniques to a variety of problems.

We start with a review of Deep Learning applications and a recap of Machine Learning tools and techniques. Then we introduce Artificial Neural Networks and explain how they are trained to solve Regression and Classification problems.

Over the rest of the course we introduce and explain several architectures including Fully Connected, Convolutional and Recurrent Neural Networks, and for each of these we explain both the theory and give plenty of example applications.

This course is a good balance between theory and practice. We don't shy away from explaining mathematical details and at the same time we provide exercises and sample code to apply what you've just learned.

The goal is to provide students with a strong foundation, not just theory, not just scripting, but both. At the end of the course you'll be able to recognize which problems can be solved with Deep Learning, you'll be able to design and train a variety of Neural Network models and you'll be able to use cloud computing to speed up training and improve your model's performance.

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Udemy

Rating 4.1 based on 258 ratings
Length 10 hours
Starts On Demand (None)
Cost $14
From Udemy
Instructors Data Weekends, Jose Portilla, Francesco Mosconi
Download Videos Only via the Udemy mobile app
Language English
Subjects Business Data Science
Tags Business Data & Analytics

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

deep learning in 39 reviews

For people already familiar with Deep Learning and probably with TensorFlow knowledge, I think this course is a nice addition.

It teaches Keras (in a shift pace, just what you need to do the job) and provides nice theoretical knowledge on difficult Deep Learning Topics.

This is a good course for an introduction to AI all the way to deep learning.

As I already had some prior knowledge regarding deep learning, I cannot accurately judge the learning pace of the course.

So, if you need a laugh once in a while, just follow the subtitles ... ;) Im summary, I'd recommend this course for any deep learning starter - a good mixture of foundations and practical application.

Tutorial makes deep learning concepts really clear and summary at end helps me to go back at whats missed.

Good kick-starter for Beginners who don't have much coding background and just want to get in to Deep Learning in no time.

This course helps me to implement Deep Learning algorithms easily.

so far in 17 reviews

Very basic so far, but we're getting there and the review material is pretty well-organized Very good and exhaustive approach of Neural Network.

Great, so far!

So fart the first few lectures are introductory and environment setup.

So far so good.

So far so good, although a bit slow.

Excellent pacing His examples are very good yes, so far a good fit the pace is a bit slow your sound and slide is easy to understand Great coding sections mixed along the course What I have watched so far has nothing in common with deep learning.

Questions do not get answered in the Q/A section for months (7 months so far).

So far it has talked about how to prepare data and set up the neural network based on Keras.

machine learning in 17 reviews

The introductory sections are very minimalistic, and in general I would not recommend this course for people with no prior machine learning or deep learning knowledge.

One of the best machine learning course that i have followed, meybe just a little too fast for someone that is completely at zero level in m-learning.

Before the review, I need to admit I have extensive knowledge of Deep and Machine Learning.

Very clear explanations, and clearly the lecturer has put in the extra effort to provide tips in how to best visualise/analyse the data based on his experience before jumping into the machine learning bits..

The course is intermediate level and having some background in machine learning going into it would be beneficial.

I strongly recommend it if you are starting to learn Neural Networks, but it is better to start with a Machine Learning Course and have some background in Python.

Although the course is not intended to learn Numpy nor Machine Learning, it would be good to have at least some links.

Compared to most other machine learning courses, I love the practical focus.

for people in 4 reviews

some of the terminology used in the course is not very welcoming for people with zero background in coding Curso ótimo This course has some good aspects such as the applications in it.

Although, it has just one drawback, that is this course is not intended for people who do not have any experience with the maths and statistics behind neural network.

Probably very hard to understand for people not already a bit familiar with neural networks and Keras.

However, still contains good information for people with some experience with Keras (i.e.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Learning Services $59k

Computer Vision, Deep Learning Engineer $67k

Computer Vision & Deep Learning Engineer $67k

Deep Clean Sales Specialist $76k

Deep clean specialist $76k

Deep Learning Research Scientist $86k

Deep Learning Research Engineer $88k

Research Scientist - Deep Learning $91k

Senior Learning Specialist, Learning and Development $102k

Deep Learning R&D Engineer $127k

Learning Assitant $142k

Deep Submergence Systems Program Manager $157k

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