# NEW course! Recommender Systems and Deep Learning in Python

September 13, 2018

### Recommender Systems and Deep Learning in Python

So excited to tell you about my new course!

Believe it or not, almost all online businesses today make use of recommender systems in some way or another.

What do I mean by “recommender systems”, and why are they useful?

Let’s look at the top 3 websites on the Internet, according to Alexa: Google, YouTube, and Facebook.

Recommender systems form the very foundation of these technologies.

YouTube: Video dashboard (and recommendations to the right of every video)

This course is a big bag of tricks that make recommender systems work across multiple platforms.

We’ll look at popular news feed algorithms, like RedditHacker News, and Google PageRank.

We’ll look at Bayesian recommendation techniques that are being used by a large number of media companies today.

But this course isn’t just about news feeds.

Companies like AmazonNetflix, and Spotify have been using recommendations to suggest products, movies, and music to customers for many years now.

These algorithms have led to billions of dollars in added revenue.

So I assure you, what you’re about to learn in this course is very real, very applicable, and will have a huge impact on your business.

For those of you who like to dig deep into the theory to understand how things really work, you know this is my specialty and there will be no shortage of that in this course. We’ll be covering state of the art algorithms like matrix factorization and deep learning (making use of both supervised andunsupervised learning), and you’ll learn a bag full of tricks to improve upon baseline results.

Whether you sell products in your e-commerce store, or you simply write a blog – you can use these techniques to show the right recommendations to your users at the right time.

If you’re an employee at a company, you can use these techniques to impress your manager and get a raise!

I’ll see you in class!

GET THE COURSE NOW

Note: this course is NOT a part of my deep learning series (it’s not Deep Learning part 11) because while it contains a major deep learning component, a lot of the course uses non-deep learning techniques as well. The deep learning parts apply modified neural network architectures and deep learning technologies to the recommender problem.

# Special Announcment: Deep Learning Keras Book!

September 12, 2018

# Simple Deep Learning for Programmers

### Learn Deep Learning via Keras examples with absolutely no math

I’m always intrigued when students tell me they want to learn deep learning without doing any math.

I was explaining to someone just yesterday – if you look at <insert famous deep learning book by famous deep learning researcher here> – the entire thing is actually cover to cover equations. Ha!

Anyhow, I wanted to test this hypothesis. How far can one get, if they try to learn deep learning via an API?

So I made this little book. It’s full of Keras examples, starting from a basic feedforward neural network, then adding some modern techniques like dropout and batch norm, then moving to more advanced architectures like CNNs and RNNs.

Of course, if you are a reader of my newsletter, you probably aren’t afraid of math!

But, I thought I’d share this book with you anyway, since it contains some interesting examples that you haven’t seen in my courses before.

– CIFAR dataset
– time series prediction using an RNN
– machine translation using a Bidirectional RNN (not a seq-to-seq model as in my Advanced NLP course)

This would also be a great opportunity to brush up on your Keras skills, which are going to be useful for my next course (hopefully coming out in a few days!)

Finally – I’ve also linked below my related book, “Simple Machine Learning for Programmers” – it is a similar experiment in teaching about machine learning using an API with no math. It’s the same as the machine learning section of my Numpy course but I know some students like to have written versions of things so they can read on the subway / airplane. If so, check it out!

August 24, 2018

# Artificial Intelligence Course Discounts Here!

August 14, 2018

#### ALL Courses on Udemy $10.99 # August 2018 ### Want to be ready for your next semester? Watch AI & Deep Learning videos! I’ve been busy making free content and updates for my existing courses, so guess what that means? Everything on sale! For the next 2 days, ALL courses on Udemy (not just mine) are available for just$10.99!

This sale won’t last long, so make sure you grab these courses while you have the chance.

For my courses, please use the coupons below (included in the links), or if you want, enter the coupon code: AUG2018.

For prerequisite courses (math, stats, Python programming) and all other courses, follow the links at the bottom.

Since ALL courses on Udemy on sale, for any course not listed here, just click the general (site-wide) link, and search for courses from that page.

ALSO: Got any requests? What do you want to learn about? (Doesn’t have to be Deep Learning or AI-related) Let me know!

https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=AUG2018

https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=AUG2018

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https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=AUG2018

https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=AUG2018

https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=AUG2018

### PREREQUISITE COURSE COUPONS

And just as important, \$10.99 coupons for some helpful prerequisite courses. You NEED to know this stuff to understand machine learning in-depth:

General (site-wide): http://bit.ly/2oCY14Z
Python http://bit.ly/2pbXxXz
Calc 1 http://bit.ly/2okPUib
Calc 2 http://bit.ly/2oXnhpX
Calc 3 http://bit.ly/2pVU0gQ
Linalg 1 http://bit.ly/2oBBir1
Linalg 2 http://bit.ly/2q5SGEE
Probability (option 1) http://bit.ly/2p8kcC0
Probability (option 2) http://bit.ly/2oXa2pb
Probability (option 3) http://bit.ly/2oXbZSK

### OTHER UDEMY COURSE COUPONS

As you know, I’m the “Lazy Programmer”, not just the “Lazy Data Scientist” – I love all kinds of programming!

iOS courses:
https://lazyprogrammer.me/ios

Android courses:
https://lazyprogrammer.me/android

Ruby on Rails courses:
https://lazyprogrammer.me/ruby-on-rails

Python courses:
https://lazyprogrammer.me/python

Big Data (Spark + Hadoop) courses:

Javascript, ReactJS, AngularJS courses:
https://lazyprogrammer.me/js

### EVEN MORE COOL STUFF

Into Yoga in your spare time? Photography? Painting? There are courses, and I’ve got coupons! If you find a course on Udemy that you’d like a coupon for, just let me know and I’ll hook you up!

# Learn PyTorch Basics: New YouTube Playlist

August 2, 2018

I’ve finally gotten around to adding a section on PyTorch basics to my course, Modern Deep Learning in Python (which already goes in-depth on Theano and Tensorflow).

As you recall, this course focuses on modern deep learning techniques such as adaptive learning rates and momentum, modern deep learning frameworks and GPU acceleration, and modern regularization techniques like dropout and batch normalization.

Check out the new videos here: