# Deep Learning BLACK FRIDAY SALE – Everything $10 November 16, 2017 A lot of you have been asking me… “When is the$10 sale coming back?”

And as you know, I share the news as soon as I find out – so here it is.

Black Friday is THE BIGGEST SALE OF THE YEAR.

This is the lowest price possible on Udemy.

I always make sure to mention to everyone: grab everything while you can because we just don’t know when the next big sale is going to be!

Don’t get stuck for months wondering… “When is the next $10 sale coming back?” Just get everything now! (Even if you don’t plan on taking the course for some time.) Enough babbling, let’s get to the coupons. Remember: there’s no need to type in the coupon code manually – I’ve already provided the links so all you need to do is click and add to cart! But just in case you’re curious – the coupon code is BLACKFRIDAY2017. Also, make sure you scroll down to the bottom for some important updates. https://www.udemy.com/data-science-linear-regression-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/data-science-logistic-regression-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/data-science-deep-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/data-science-natural-language-processing-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/sql-for-marketers-data-analytics-data-science-big-data/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/cluster-analysis-unsupervised-machine-learning-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/unsupervised-deep-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/unsupervised-machine-learning-hidden-markov-models-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/deep-learning-recurrent-neural-networks-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/machine-learning-in-python-random-forest-adaboost/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=BLACKFRIDAY2017 https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=BLACKFRIDAY2017 MODERN DEEP LEARNING IN PYTHON VIP VERSION In my last post, I relaunched my course “Modern Deep Learning in Python” which has more than doubled in size since its inception. Along with this re-release I offered a special VIP version of the course where you get a free 28-page tutorial on Tensorflow’s new Estimator API. As mentioned, this deal is not going to last. In fact, 24 hours from now, it will be GONE FOREVER. Remember: you MUST use the VIP coupon to get the VIP material. PREREQUISITE COURSE COUPONS And just as important,$10 coupons for some helpful prerequisite courses. You NEED to know this stuff before you study machine learning:

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/2prFQ7o
Probability (option 2) http://bit.ly/2p8kcC0
Probability (option 3) http://bit.ly/2oXa2pb
Probability (option 4) 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!

And I’ve got sales for everything:

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!
Remember, these links will self-destruct on November 28 (13 days). Act NOW!

# Modern Deep Learning in Python – RELAUNCH and VIP version!

November 12, 2017

If you’ve been following my updates, you may have noticed that I’ve been hard at work doubling the size of my course, “Deep Learning part 2”, otherwise known as “Practical Deep Learning in Theano and Tensorflow”.

I’ve since renamed the course to “Modern Deep Learning in Python” and I am officially re-launching it today!

At this point, I have completed all the major updates I’ve had in my pipeline: extending the modern regularization section, adding batch normalization, Adam, and more code for other modern libraries like Keras, PyTorch, CNTK, and MXNet.

As part of this relaunch, I am releasing a VIP version of this course.

What do you get?

Well, in addition to the HOURS of free content I’ve just added to the course, you may have heard of Tensorflow’s new Estimator API.

It was released just a few months ago.

Why is it better?

• Greatly simplifies machine learning programming
• No need to deal with Graphs or Sessions
• Encapsulates training, evaluation, prediction, and exporting models
• Provides standard models so you don’t have to write any of the code yourself

You may have noticed that writing Tensorflow code can be quite repetitive. We need to define each layer, combine the layers to calculate the output, create a loss function, create an optimizer, initialize the variables, run the optimizer, plot the loss, and so on.

All “boilerplate” stuff (although helpful to repeat if you are in the process of learning Tensorflow).

But while the Estimator API simplifies machine learning programming, it is not necessarily easy. And hence, I’ve written a 28-page tutorial to teach you how to use it from the ground up.

We start out with the Sci-Kit Learn API, and gradually build on those ideas to familiarize ourselves with the new Estimator API.

We go through a FULL CODE example on a dataset NEVER-BEFORE SEEN in my courses. Some new data wrangling techniques will be taught, in particular: the “hashing trick” and how to create embeddings instead of one-hot encoding categorical variables.

To get the VIP version of Modern Deep Learning in Python, just go here: https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=IAMAVIP2

[Note: make SURE you use the coupon code IAMAVIP2 – those who do not use the code will not get the VIP material!]

Now I realize that a lot of you might already be signed up for this course. That means, you get all the updated content for free and have been seeing the updates come through as I’ve added them. Woohoo!

If you support the work I’ve been doing on adding many hours of free updates to the courses you’ve already purchased, then consider signing up for the course at https://deeplearningcourses.com/c/data-science-deep-learning-in-theano-tensorflow

I’ve temporarily decreased the price to $10. Courses on deeplearningcourses.com will always contain the extra VIP material. You can think of it like a small donation as a token of appreciation, but don’t forget you are still getting this 28-PAGE easy-to-follow tutorial on the Estimator API. Believe me, I’ve looked at other resources out there – they were not fun reading. So, if you are already a student of Modern Deep Learning in Python and you would like to access the VIP stuff, get it now! This price won’t last. To be sure: I still have TONS of stuff I still want to add to this course and my other courses. So much that sometimes I wonder how I’m going to get it all done! If you support this effort and you want to see MORE of it in the future, please do consider getting the VIP version of this course. I am very thankful for all the support! Note: if you order the VIP version of the course through Udemy, you should receive a link to the VIP material within 24 hours of purchase in your message inbox. So don’t forget to check your messages! Shoot me a message if you haven’t got your VIP material by that time. Go to comments # Deep Learning Halloween SALE! 90% OFF ALL Udemy Courses October 29, 2017 ### Huge updates ahead I’ve been really busy adding tons of free updates to my existing courses. You can scroll down to the very bottom to see what they are. But in the mean time we are going to do another HUGE sale. ALL courses on Udemy are now$12. Take this opportunity to grab as many courses as you can because you never know when the next sale is going to be!

As usual, I’m providing $12 coupons for all my courses in the links below. Please use these links and share them with your friends! You can also just type in the coupon code “OCT456”. The promo goes until October 31. Don’t wait! At the end of this post, I’m going to provide you with some additional links to get machine learning prerequisites (calculus, linear algebra, Python, etc…) for$12 too!

But that’s not all… I’m the Lazy Programmer, not just the Lazy Data Scientist – I’ve got $12 coupons for iOS development, Android development, Ruby on Rails, Python, Big Data / Hadoop / Spark, React.js, Angular, and MORE. All important skillsets on ANY engineering team. Got any friends or coworkers in mobile / backend / big data development? Let them know! If you don’t know what order to take the courses in, please check here: https://deeplearningcourses.com/course_order  Deep Learning: GANs and Variational Autoencoders https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=OCT456  Advanced AI: Deep Reinforcement Learning in Python https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=OCT456  Artificial Intelligence: Reinforcement Learning in Python https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=OCT456  Bayesian Machine Learning in Python: A/B Testing https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=OCT456  Cluster Analysis and Unsupervised Machine Learning in Python https://www.udemy.com/cluster-analysis-unsupervised-machine-learning-python/?couponCode=OCT456  Deep Learning: Convolutional Neural Networks in Python https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/?couponCode=OCT456  Deep Learning in Python https://www.udemy.com/data-science-deep-learning-in-python/?couponCode=OCT456  Practical Deep Learning in Theano and TensorFlow https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=OCT456  Advanced Natural Language Processing: Deep Learning in Python https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=OCT456  Ensemble Machine Learning in Python: Random Forest and AdaBoost https://www.udemy.com/machine-learning-in-python-random-forest-adaboost/?couponCode=OCT456  Unsupervised Machine Learning: Hidden Markov Models in Python https://www.udemy.com/unsupervised-machine-learning-hidden-markov-models-in-python/?couponCode=OCT456  Deep Learning Prerequisites: Linear Regression in Python https://www.udemy.com/data-science-linear-regression-in-python/?couponCode=OCT456  Deep Learning Prerequisites: Logistic Regression in Python https://www.udemy.com/data-science-logistic-regression-in-python/?couponCode=OCT456  Data Science: Natural Language Processing in Python https://www.udemy.com/data-science-natural-language-processing-in-python/?couponCode=OCT456  Deep Learning: Recurrent Neural Networks in Python https://www.udemy.com/deep-learning-recurrent-neural-networks-in-python/?couponCode=OCT456  SQL for Newbs and Marketers https://www.udemy.com/sql-for-marketers-data-analytics-data-science-big-data/?couponCode=OCT456  Data Science: Supervised Machine Learning in Python https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=OCT456  Unsupervised Deep Learning in Python https://www.udemy.com/unsupervised-deep-learning-in-python/?couponCode=OCT456  PREREQUISITE COURSE COUPONS And just as important,$12 coupons for some helpful prerequisite courses. You NEED to know this stuff before you study machine learning: 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/2prFQ7o Probability (option 2) http://bit.ly/2p8kcC0 Probability (option 3) http://bit.ly/2oXa2pb Probability (option 4) 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! And I’ve got sales for everything: 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: https://lazyprogrammer.me/big-data-hadoop-spark-sql 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!       COURSE UPDATES Recent updates to existing courses because my students are awesome and deserve free stuff: Deep Learning pt 2: More lectures on hyperparameter optimization Deep Learning pt 2: Keras!!! (very popular request) Deep Learning pt 2: Noise injection Deep Learning pt 1: Why Learn the Ins and Outs of Backpropagation? All relevant courses: How to uncompress a .tar.gz file Remember, these links will self-destruct on October 31 (4 days). Act NOW!

# Deep Learning: The Swish Activation Function

October 18, 2017

The Google Brain team has just released a new paper (https://arxiv.org/abs/1710.05941) that demonstrates the superiority of a new activation function called Swish on a number of different neural network architectures.

This is interesting because people often ask me, “which activation function should I use?”

These days, it is common to just use the ReLU by default.

To refresh your memory, the ReLU looks like this:

And it is defined by the equation:

$$f(x) = max(0, x)$$

One major problem with the ReLU is that its derivative is 0 for half the values of the input $$x$$. Because we use “gradient descent” as our parameter update algorithm, if the gradient is 0 for a parameter, then that parameter will not be updated!

In other words, when I do:

$$\theta = \theta – \alpha \frac{\partial J}{\partial \theta }$$

And:

$$\frac{\partial J}{\partial \theta } = 0$$

Then my update is just:

$$\theta = \theta$$

Which just assigns the parameter back to itself.

This leads to the problem of “dead neurons”. Experiments have shown that neural networks trained with ReLUs can have up to 40% dead neurons!

There have been some proposed alternatives to this, such as the leaky ReLU, the ELU, and the SELU.

Interestingly, none of these have seemed to catch on and it’s still ReLU by default.

So how does the Swish activation function work?

The function itself is very simple:

$$f(x) = x \sigma(x)$$

Where $$\sigma(x)$$ is the usual sigmoid activation function.

$$\sigma(x) = (1 + e^{-x})^{-1}$$

It looks like this:

What’s interesting about this is that unlike every other activation function, it is not monotonically increasing. Does it matter? It seems the answer is no!

The derivative looks like this:

One interesting thing we can do is re-parameterize the Swish, in order to “stretch out” the sigmoid:

$$f(x) = 2x \sigma(\beta x)$$

We can see that, if $$\beta = 0$$, then we get the identity activation $$f(x) = x$$, and if $$\beta \rightarrow \infty$$ then the sigmoid converges to the unit step and multiplying that by $$x$$ gives us back $$f(x) = 2 max(0, x)$$ which is just the ReLU multiplied by a constant factor.

So including $$\beta$$ is a way for us to nonlinearly interpolate between identity and ReLU.

The title of the paper is “A Self-Gated Activation Function”, which might make you wonder, “Why is it self-gated?”

This should remind you of the LSTM, where we have “gates” in the form of sigmoids that control how much of a vector gets passed on to the next stage, by multiplying it between the output of the sigmoid, which is a number between 0 and 1.

So “self-gated” means that the gate is just the sigmoid of the activation itself.

Gate: $$\sigma(x)$$

Value to pass through: $$x$$

But that’s enough theory. For most of us, we want to know: “Does it work?”

And more practically, “Can I just use this by default instead of the ReLU?”

The best thing to do is just to try it for yourself and see how robust it is to different settings of hyperparameters (learning rate, architecture, etc.) but let’s look at some results so we can be confident when it comes to using Swish:

Click on the image to see it in the original size.

To compare Swish with baseline, a statistical test called the one-sided paired sign test was used.

Conclusion: Try Swish for yourself!

# Python 2-to-3 Tips

October 17, 2017

This is a short post to help those of you who need help translating code from Python 2 to Python 3.

Python 2 is the most popular Python version (at least at this time and certainly at the time my courses were created), hence why it was used.

It comes with Mac OS and Ubuntu pre-installed so when you type in “python” into your command line, you get Python 2.

This list is not exhaustive. It shows only code that appears commonly in my machine learning scripts, to assist the students taking my machine learning courses (https://deeplearningcourses.com).

Integer Division

OLD:

a / b

NEW:

a // b

For Loops

OLD:

for i in xrange

NEW:

for i in range

Printing

OLD:

print "hello world"

NEW:

print("hello world")

# Deep Learning and Machine Learning FALL SALE 90% OFF

October 7, 2017

“Hey Lazy Programmer, when is your next course coming out?”

I’ve been really busy adding tons of free updates to my existing courses! You can scroll down to the very bottom to see what they are. But in the mean time we are going to do another HUGE sale. ALL courses on Udemy are now $12. Take this opportunity to grab as many courses as you can because you never know when the next sale is going to be! As usual, I’m providing$12 coupons for all my courses in the links below. Please use these links and share them with your friends!

You can also just type in the coupon code “OCT123” (except Deep Learning pt 1 because I messed it up =), for that use “OCT123A”).

The promo goes until October 10. Don’t wait!

At the end of this post, I’m going to provide you with some additional links to get machine learning prerequisites (calculus, linear algebra, Python, etc…) for $12 too! But that’s not all… I’m the Lazy Programmer, not just the Lazy Data Scientist – I’ve got$12 coupons for iOS development, Android development, Ruby on Rails, Python, Big Data / Hadoop / Spark, React.js, Angular, and MORE. All important skillsets on ANY engineering team. Got any friends or coworkers in mobile / backend / big data development? Let them know!

If you don’t know what order to take the courses in, please check here: https://deeplearningcourses.com/course_order
Here are the links for my courses:

Deep Learning Prerequisites: Linear Regression in Python
https://www.udemy.com/data-science-linear-regression-in-python/?couponCode=OCT123

Deep Learning Prerequisites: Logistic Regression in Python
https://www.udemy.com/data-science-logistic-regression-in-python/?couponCode=OCT123

Deep Learning in Python
https://www.udemy.com/data-science-deep-learning-in-python/?couponCode=OCT123A

Practical Deep Learning in Theano and TensorFlow
https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=OCT123

Deep Learning: Convolutional Neural Networks in Python
https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/?couponCode=OCT123

Unsupervised Deep Learning in Python
https://www.udemy.com/unsupervised-deep-learning-in-python/?couponCode=OCT123

Deep Learning: Recurrent Neural Networks in Python
https://www.udemy.com/deep-learning-recurrent-neural-networks-in-python/?couponCode=OCT123

Advanced Natural Language Processing: Deep Learning in Python
https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=OCT123

Advanced AI: Deep Reinforcement Learning in Python
https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=OCT123

Deep Learning: GANs and Variational Autoencoders
https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=OCT123

Easy Natural Language Processing in Python
https://www.udemy.com/data-science-natural-language-processing-in-python/?couponCode=OCT123

Cluster Analysis and Unsupervised Machine Learning in Python
https://www.udemy.com/cluster-analysis-unsupervised-machine-learning-python/?couponCode=OCT123

Unsupervised Machine Learning: Hidden Markov Models in Python
https://www.udemy.com/unsupervised-machine-learning-hidden-markov-models-in-python/?couponCode=OCT123

Data Science: Supervised Machine Learning in Python
https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=OCT123

Bayesian Machine Learning in Python: A/B Testing
https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=OCT123

Ensemble Machine Learning in Python: Random Forest and AdaBoost

Artificial Intelligence: Reinforcement Learning in Python
https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=OCT123

SQL for Newbs and Marketers
https://www.udemy.com/sql-for-marketers-data-analytics-data-science-big-data/?couponCode=OCT123

PREREQUISITE COURSE COUPONS

And just as important, $12 coupons for some helpful prerequisite courses. You NEED to know this stuff before you study machine learning: 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/2prFQ7o Probability (option 2) http://bit.ly/2p8kcC0 Probability (option 3) http://bit.ly/2oXa2pb Probability (option 4) 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! And I’ve got sales for everything: 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: https://lazyprogrammer.me/big-data-hadoop-spark-sql 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! Remember, these links will self-destruct on October 10 (5 days). Act NOW! COURSE UPDATES Recent updates to existing courses because my students are awesome and deserve free stuff: Deep Learning pt 2 (Theano / Tensorflow): * Brand new section on batch normalization (7 new lectures!) Deep Reinforcement Learning (Advanced AI): * Continuous Mountain Car in Theano and Tensorflow with Policy Gradient Cluster Analysis / Unsupervised ML: * Simulating Biological Evolution + Applying Clustering * Applying Clustering to Donald Trump + Hillary Clinton Tweets from 2016 Election Numpy Stack: * Improved quality / resolution of all slides * Pushed code up so video player controls won’t block it Unsupervised Deep Learning * Visualizing t-SNE Go to comments # Goodbye Theano September 29, 2017 It’s a sad day for us Theano fans. The developers of Theano have announced that they are halting development following the 1.0 release. Here’s the original post: https://groups.google.com/forum/#!topic/theano-users/7Poq8BZutbY Dear users and developers, After almost ten years of development, we have the regret to announce that we will put an end to our Theano development after the 1.0 release, which is due in the next few weeks. We will continue minimal maintenance to keep it working for one year, but we will stop actively implementing new features. Theano will continue to be available afterwards, as per our engagement towards open source software, but MILA does not commit to spend time on maintenance or support after that time frame. The software ecosystem supporting deep learning research has been evolving quickly, and has now reached a healthy state: open-source software is the norm; a variety of frameworks are available, satisfying needs spanning from exploring novel ideas to deploying them into production; and strong industrial players are backing different software stacks in a stimulating competition. We are proud that most of the innovations Theano introduced across the years have now been adopted and perfected by other frameworks. Being able to express models as mathematical expressions, rewriting computation graphs for better performance and memory usage, transparent execution on GPU, higher-order automatic differentiation, for instance, have all become mainstream ideas. In that context, we came to the conclusion that supporting Theano is no longer the best way we can enable the emergence and application of novel research ideas. Even with the increasing support of external contributions from industry and academia, maintaining an older code base and keeping up with competitors has come in the way of innovation. MILA is still committed to supporting researchers and enabling the implementation and exploration of innovative (and sometimes wild) research ideas, and we will keep working towards this goal through other means, and making significant open source contributions to other projects. Thanks to all of you who for helping develop Theano, and making it better by contributing bug reports, profiles, use cases, documentation, and support. — Yoshua Bengio, Head of MILA Go to comments # Deep Learning and Machine Learning September 2017 Coupons September 13, 2017 Since I am still busy hacking away at my next course, we are going to do another HUGE sale. ALL courses on Udemy are now$12. Take this opportunity to grab as many courses as you can because you never know when the next sale is going to be!

As usual, I’m providing $12 coupons for all my courses in the links below. Please use these links and share them with your friends! You can also just type in the coupon code “SEP123”. The promo goes until September 20. Don’t wait! At the end of this post, I’m going to provide you with some additional links to get machine learning prerequisites (calculus, linear algebra, Python, etc…) for$12 too!

But that’s not all… I’m the Lazy Programmer, not just the Lazy Data Scientist – I’ve got $12 coupons for iOS development, Android development, Ruby on Rails, Python, Big Data / Hadoop / Spark, React.js, Angular, and MORE. All important skillsets on ANY engineering team. Got any friends or coworkers in mobile / backend / big data development? Let them know! If you don’t know what order to take the courses in, please check here: https://deeplearningcourses.com/course_order Here are the links for my courses: Deep Learning Prerequisites: Linear Regression in Python https://www.udemy.com/data-science-linear-regression-in-python/?couponCode=SEP123 Deep Learning Prerequisites: Logistic Regression in Python https://www.udemy.com/data-science-logistic-regression-in-python/?couponCode=SEP123 Deep Learning in Python https://www.udemy.com/data-science-deep-learning-in-python/?couponCode=SEP123 Practical Deep Learning in Theano and TensorFlow https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=SEP123 Deep Learning: Convolutional Neural Networks in Python https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/?couponCode=SEP123 Unsupervised Deep Learning in Python https://www.udemy.com/unsupervised-deep-learning-in-python/?couponCode=SEP123 Deep Learning: Recurrent Neural Networks in Python https://www.udemy.com/deep-learning-recurrent-neural-networks-in-python/?couponCode=SEP123 Advanced Natural Language Processing: Deep Learning in Python https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=SEP123 Advanced AI: Deep Reinforcement Learning in Python https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=SEP123 Deep Learning: GANs and Variational Autoencoders https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=SEP123 Easy Natural Language Processing in Python https://www.udemy.com/data-science-natural-language-processing-in-python/?couponCode=SEP123 Cluster Analysis and Unsupervised Machine Learning in Python https://www.udemy.com/cluster-analysis-unsupervised-machine-learning-python/?couponCode=SEP123 Unsupervised Machine Learning: Hidden Markov Models in Python https://www.udemy.com/unsupervised-machine-learning-hidden-markov-models-in-python/?couponCode=SEP123 Data Science: Supervised Machine Learning in Python https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=SEP123 Bayesian Machine Learning in Python: A/B Testing https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=SEP123 Ensemble Machine Learning in Python: Random Forest and AdaBoost https://www.udemy.com/machine-learning-in-python-random-forest-adaboost/?couponCode=SEP123 Artificial Intelligence: Reinforcement Learning in Python https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=SEP123 SQL for Newbs and Marketers https://www.udemy.com/sql-for-marketers-data-analytics-data-science-big-data/?couponCode=SEP123 PREREQUISITE COURSE COUPONS And last but not least,$12 coupons for some helpful prerequisite courses. You NEED to know this stuff before you study machine learning:

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/2prFQ7o
Probability (option 2) http://bit.ly/2p8kcC0
Probability (option 3) http://bit.ly/2oXa2pb
Probability (option 4) 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!

And I’ve got sales for everything:

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!

Remember, these links will self-destruct on September 20 (7 days). Act NOW!

# Deep Learning $10 Udemy coupons + LAST DAY for VIP bonus August 21, 2017 It’s that time again! BIG DISCOUNTS for everyone! If you’re in the USA you should see$10 coupons. If you’re in another country you’ll see the corresponding amount in your own currency.

But before we get to that, I want to mention that the VIP bonus for my latest Deep Learning course on GANs and Variational Autoencoders is CLOSING TODAY.

So if you want to get the VIP bonus and you haven’t gotten it yet, NOW is the time!

Just a reminder of what you get:

1) PDF cheatsheet / tutorial on Variational Autoencoders for your reading convenience

2) PDF cheatsheet / tutorial on GANs for your reading convenience (with exercises)

3) Pre-trained style transfer network! No need to train for 4 months on your slow CPU, or pay hundreds of dollars to use a GPU, or download 100s of MBs of Tensorflow checkpoint data! I’ve condensed the neural network weights to a few MBs so you can get going right away.

If you don’t know what “style transfer” is – that’s where I train a neural network to learn the “style” of Picasso or Da Vinci, and then apply it to a completely unrelated image like the Chicago skyline.

Very cool application of neural networks!

Remember: these VIP bonuses are ONLY available if you use the VIP coupon, which is automatically applied when you click this link:

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

Now, for the regular $10 discounts (check the end of this newsletter for how to get$10 coupons for ANY course on Udemy this week!):

Deep Learning Prerequisites: Linear Regression in Python https://www.udemy.com/data-science-linear-regression-in-python/?couponCode=AUG456​

Deep Learning Prerequisites: Logistic Regression in Python https://www.udemy.com/data-science-logistic-regression-in-python/?couponCode=AUG456​

Deep Learning in Python https://www.udemy.com/data-science-deep-learning-in-python/?couponCode=AUG456​

Practical Deep Learning in Theano and TensorFlow https://www.udemy.com/data-science-deep-learning-in-theano-tensorflow/?couponCode=AUG456​

Deep Learning: Convolutional Neural Networks in Python https://www.udemy.com/deep-learning-convolutional-neural-networks-theano-tensorflow/?couponCode=AUG456​

Unsupervised Deep Learning in Python https://www.udemy.com/unsupervised-deep-learning-in-python/?couponCode=AUG456​

Deep Learning: Recurrent Neural Networks in Python https://www.udemy.com/deep-learning-recurrent-neural-networks-in-python/?couponCode=AUG456​

Advanced Natural Language Processing: Deep Learning in Python https://www.udemy.com/natural-language-processing-with-deep-learning-in-python/?couponCode=AUG456​

Advanced AI: Deep Reinforcement Learning in Python https://www.udemy.com/deep-reinforcement-learning-in-python/?couponCode=AUG456​

Easy Natural Language Processing in Python https://www.udemy.com/data-science-natural-language-processing-in-python/?couponCode=AUG456​

Cluster Analysis and Unsupervised Machine Learning in Python https://www.udemy.com/cluster-analysis-unsupervised-machine-learning-python/?couponCode=AUG456​

Unsupervised Machine Learning: Hidden Markov Models in Python https://www.udemy.com/unsupervised-machine-learning-hidden-markov-models-in-python/?couponCode=AUG456​

Data Science: Supervised Machine Learning in Python https://www.udemy.com/data-science-supervised-machine-learning-in-python/?couponCode=AUG456​

Bayesian Machine Learning in Python: A/B Testing https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=AUG456​

Artificial Intelligence: Reinforcement Learning in Python https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=AUG456​

Deep Learning: GANs and Variational Autoencoders https://www.udemy.com/deep-learning-gans-and-variational-autoencoders/?couponCode=AUG456

SQL for Newbs and Marketers https://www.udemy.com/sql-for-marketers-data-analytics-data-science-big-data/?couponCode=AUG456​

PREREQUISITE COURSE COUPONS

Last but not least, \$10 coupons for some helpful prerequisite courses. You NEED to know this stuff before you study machine learning:

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/2prFQ7o
Probability (option 2) http://bit.ly/2p8kcC0
Probability (option 3) http://bit.ly/2oXa2pb
Probability (option 4) 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!

If you have friends who are into any of these topics, do them a favor and let them know about these amazing discounts:

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!

Remember, these links will self-destruct on August 31 (10 days). Act NOW!

# NEW Deep Learning Course: GANs and Variational Autoencoders

August 1, 2017

You asked for it, and it’s here!

I am pleased to announce my latest course:

Deep Learning: Variational Autoencoders and GANs

GANs have been called one of the most interesting developments in deep learning in 2016.

This is coming from Yann LeCun – one of the grandmasters of deep learning.

Most of you already know why GANs are cool – that’s why you’ve been asking me for this course.

But just in case you don’t:

GANs are notable for being able to produce extremely high-quality, high-resolution, sharp samples.

We’ve had neural networks (and non-deep learning ML algorithms) that can generate samples for decades… but none come close to the quality of images generated by GANs.

This is some Jason Bourne-level stuff… you know how they “enhance” a tiny / blurry image from some government spy camera?

Guess what can actually do that? GANs.

Fun fact: a group of Harvard PhDs JUST did an AMA on Reddit this week. Check out what one had to say about Unsupervised Deep Learning:

There are a ton of more cool applications that we’ll discuss in the course like reinforcement learning. This stuff is basically the latest-and-greatest in deep learning.

Why variational autoencoders and not just GANs? Both of these neural networks fall into the category of “deep neural network samplers” – they both attempt to learn the structure of data in some way, which you can then use to generate new data that mimics what was learned.

I think variational autoencoders are super cool because they combine 2 of my favorite subjects: deep learning and Bayesian machine learning.

They were also invented at approximately the same time and are always mentioned in the context of one another, so in some sense they belong in the same “family” of algorithms.

Another cool thing about this course: a surprising lack of prerequisites! Technically, this will be Deep Learning part 8 and Unsupervised Deep Learning part 2. But, you won’t need to know anything from Deep Learning part 5, 6, or 7, nor Unsupervised Deep Learning part 1 (which is also Deep Learning part 4). You will need to know how to build convolutional neural networks and have a working understanding of Bayes classifiers, but that’s pretty much it! Not that learning how to build convolutional neural networks was an easy place to get to, but now that you’re there, you can breathe easy.

Now, this course is going to be available to all students on Udemy, but if you’re receiving this email, that means you’ve already taken a course of mine, which is why I am offering you something exclusive: The VIP version of this course.

It will ONLY be available to students who use this link, which applies a special coupon that I can check that you used:

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

What’s in it?

VIP EXTRAS

Here’s what you get if you sign up for the VIP version of the course:

Because I am such a geek, I decided to use LaTeX to create short, concise tutorials for both the GAN and variational autoencoder.

These will be great to help you review the material and ingest it in a different format, no doubt increasing your understanding of what you learn in the course.

You can take it with you on the train and read it at your leisure!

But that’s not all…

One of the COOLEST applications of neural networks that just “learn the structure of data” (as opposed to trying to assign labels to it) is STYLE TRANSFER.

Ever wanted to know what the New York City skyline would look like if it were painted by Picasso?

Now you can find out!

Style transfer networks are neural networks that learn the “essence” or “style” of one image, and then have the ability to apply that same style to new images.

I find this to be one of the most FASCINATING applications of using deep learning to learn the structure of data.

Of course… for most of us, such a neural network would take around 4 months to train…

So here’s what you get for signing up for the VIP special:

A SUPER SIMPLE script you can just run, which automatically downloads pre-trained neural network weights for 3 different styles (Dora Maar, Rain Princess, and Starry Night), which you can then use to apply those styles to ANY input image within SECONDS.

The neural network accepts any size input image because all the weights are convolutional filters!

How cool is that?

And it’s in Tensorflow, so all you Windows users out there don’t feel left out. =)

And remember: these VIP specials are only available IF you use the VIP COUPON (IAMAVIP) – so make sure you use the coupons / links in this email, otherwise, you will not get the VIP bonuses!

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

Quick note: If you don’t receive the VIP extras right away, don’t worry. I will be going through the list myself, you WILL get them.

#deep learning #gans #unsupervised learning #variational autoencoders