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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 357 ratings
Length 10 total hours
Starts On Demand (Start anytime)
Cost $11
From Udemy
Instructors Data Weekends, Jose Portilla, Francesco Mosconi
Download Videos Only via the Udemy mobile app
Language English
Subjects Data Science Business
Tags Data Science Business Development Data & Analytics

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What people are saying

According to other learners, here's what you need to know

deep learning in 51 reviews

This help me pick up the Deep Learning concepts very quickly and implement them on Keras.

The course give me lots of necessary informations about Deep Learning.

One of the better Deep Learning courses I have done to explain the core concepts well.

Really good, very good grounding in deep learning introducing the topics and giving some excellent exercises to fully understand them.

This was a great coarse that hit many critical points on how to train a deep learning model.

it is really good due to I work with a lot data that would be used to build good model by Deep learning Absolutely fantastic course.

I would highly recommend it to anyone looking to learn deep learning.

tone of sound is a bit boring given the topic is so exciting ;) Should have more python and keras concept regarding deep learning His lecture is well-structured, and well-organized.

Trying to understand the concept of deep learning, this course is helping me understand the applications and algorithm involved in deep learning May require a little background in calculus or optimization to understand fully but does a better job of describing DL than most resources Great depth of concepts.

Excellent examples of Deep learning an the applications in the real world Going good, interesting examples very thorough!

This course helps me to implement Deep Learning algorithms easily.

Instructor should focus on making a new course like 'Advanced use of CNN, RNN using Keras' i wanna give 5 star but look like instructor abandon his course in lecture vanishing gradient decent say coming soon for 3 month it's not soon at all i don't know why he doesn't update it yet by the way this is a good introduction course good content i will suggest to the one who new to deep learning anyway as well as intro to keras This was a very helpful course.

I appreciate this introduction to Deep Learning and the practice in Keras.

Personally, I just want to focus on trying some deep learning models, gain an understanding, and make use of the tools.

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machine learning in 19 reviews

It's an awesome course for people who first starts Machine Learning topics Missing a few execersizes solutions inhalte sehr gut, Lösungen zu manchen Aufgaben fehlen leider Content interesting, well chosen and well explained.

well guided intro to machine learning.

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

The course is good however some lectures are missing and I hope will some soon Compared to most other machine learning courses, I love the practical focus.

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.

My main concerns are related to the shallowness with which the field of machine learning is presented.

A real tour de force of machine learning.

Strong points are; uses keras, uses juypter notebook, contains recent techniques, introduces varied datasets including examples of mild failure cases of machine learning.

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

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..

I felt that this course was reasonable for someone that has a background in math, Python, and machine learning.

from Machine Learning A-Z course).

This course is great if you don't want to actually learn what is happening behind the models and API's, and if you just want a brief overview of Machine Learning to get started on a project that you have in mind.

Excellent course, this is a great introduction for a programming student who wishes to learn more about machine learning.

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so far so good in 7 reviews

So far so good.

:) So far so good.

So far really enjoying it, instructor does a good job of covering the basics before starting into the deep learning topics So far so good, although a bit slow.

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easy to understand in 9 reviews

Easy to understand and backed by moderate mathematical principles behind neural networks.

but there are some missing solutions... Instructor is easy to understand and the class is broken very well into functional need to know components.

It's rather easy to understand, but it is a bit slower, after hours of learning, I am still in basic knowledge of python, and it seems I need several hours before really touch deep learning.

Incredibly clear, easy to understand examples.

very good clear, step by step guidance, very practical Easy to understand.

clear video and instructions your sound and slide is easy to understand Good job~ Basic stuff yes, so far a good fit Easy to understand very clear and easy to understand.

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recommend this course in 5 reviews

I recommend this course after taking at least one easier beginner course so that you can understand more clearly.

I'd highly recommend this course if you've taken Jose Portilla's Machine Learning Bootcamp with Python.

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.

This is amazing course, I do have taken other courses on Deep Learning too but i would recommend this course.

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neural networks in 7 reviews

However, the underlying concepts of Neural Networks are not changed.

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.

I was debating taking off half a star because I had difficulty with some of the explanations not being explicitly clear, but decided against it because I realized that it is inevitable you have to rely on more than one source to get to a deep level of understanding with neural networks.

You don't need any previous experience with neural networks, just as advertised.

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

Besides that this course has helped me to set up Keras and Deep Neural Networks using it.

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code along in 4 reviews

Course contains many useful information and great code along as well as exercises to make sure leaner gets familiar with knowledge.

Finally, I need to highlight that to be successful one needs to do homework at the end of every chapter and also code along the code along pieces.

I really enjoyed this course, able to follow with the instructor, liked the way the code along sections are explained Excelente curso sobre Keras e Python.

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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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Udemy

Rating 4.1 based on 357 ratings
Length 10 total hours
Starts On Demand (Start anytime)
Cost $11
From Udemy
Instructors Data Weekends, Jose Portilla, Francesco Mosconi
Download Videos Only via the Udemy mobile app
Language English
Subjects Data Science Business
Tags Data Science Business Development Data & Analytics

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