Deep Learning with Python and Keras (Udemy.com)

Understand and build Deep Learning models for images, text and more using Python and Keras

( 312 Reviews )

Created by: Data Weekends

Produced in 2018

What you will learn

To describe what Deep Learning is in a simple yet accurate way
To explain how deep learning can be used to build predictive models
To distinguish which practical applications can benefit from deep learning
To install and use Python and Keras to build deep learning models
To apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data.
To build, train and use fully connected, convolutional and recurrent neural networks
To look at the internals of a deep learning model without intimidation and with the ability to tweak its parameters
To train and run models in the cloud using a GPU
To estimate training costs for large models
To re-use pre-trained models to shortcut training time and cost (transfer learning)

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 84 / 100

Course Description

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.

Thiscourse 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.

Who this course is for:
Software engineers who are curious about data science and about the Deep Learning buzz and want to get a better understanding of itData scientists who are familiar with Machine Learning and want to develop a strong foundational knowledge of deep learning

Time: 10h

Instructor Details

Data Weekends

4.2 Rating
312 Reviews

Data Weekends are accelerated data science workshop for programmers where you can quickly learn to apply predictive analytics to real-world data. We offer courses in Data Analytics, Machine Learning, Deep Learning and Reinforcement Learning.
Through our parent company Catalit LLC we also offer corporate training and consulting on Data Science, Machine Learning and Deep Learning.

Data Weekends' founder and lead instructor is Francesco Mosconi, PhD.

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Reviews

4.2

312 total reviews

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Write a Review

By C Barbosa on 9/27/2020

The name of this course is wrong... it should be "introduction on artificial intelligence" Very few and irrelevant information about Keras or Tensorflow.

By Setareh Behzadipishkenari on 9/23/2020

The course is pretty good and usefull. Tnx a lot

By William Bardwell on 9/9/2020

This course is an excellent tool to assist me to learn deep learning

By Rahul Kumar on 8/23/2020

I opted for the course based on the ratings it had. Turns out, this is at max an average course on deep learning. The trainer has tried really hard to explain concepts but they don't go with real world and he doesn't give any background on the concepts. He has taught this course as like reading from any manual without having any real world experience. I'd highly recommend to look for other course on the topic.

By Wouter Meijer on 8/22/2020

A lot of new material, has to stay very focused to be able to follow all the steps. Fortunately, the course leaves room for my own way of learning. The subtitles of a video are sometimes disturbing with language errors.
Tensor flow playground helped to make a neural network less abstract and more transparent.

By Muhammad Shahzad Khan on 8/22/2020

It was a really good experience. A very well explained each and everything for a novice person to learn Deep Learning using Keras.

By Allan Angulo on 7/25/2020

Buena eleccin, hacen faltan unas lecciones.

By Can Ozay on 7/22/2020

yes, good and informative. more details would be better but a bit early conclusion at this point and still needs to go with next 95 videos

By Matthew Afsahi on 7/22/2020

I have got this course because I thought Jose will be teaching this course as he is very good at teaching and explaining the materials, unfortunately this course was not that useful for me and my learning progress.

By Viktor Semenov on 7/11/2020

Very nice course. Well designed and very well thought. I would put 5 star, but the course a little bit not finished

By Guilherme Mendona Freire on 7/9/2020

Nice. So far.

By Ryan Keck on 7/9/2020

The material of the course was pretty good. However, it doesn't look like questions have been answered by the instructor in the last year. The course also seems kind of unfinished. A few of the solutions do not have videos at the end, it just says "coming soon" or something.
Regarding the exercises, I'm a little bit torn. I wish they were a little bit more specific, since I'm mostly just trying to get an understanding of the code and how to make things run. That being said, if you've never had to fiddle with things to make them work, the exercises will be a painful but worthwhile experience. Essentially, the exercises are probably a lot closer to what you'll see in the real world. Most other courses hold your hand through the exercises, but not here. This is probably not a good first course in machine learning, but if you've gone through another course or two, this should add on to the foundation really well. The course has things I didn't see in other courses. I highly recommend looking at the course at some point, but I would wait for a sale or something, I can't recommend at full price.