# Boston Dynamics – Introducing Handle

February 28, 2017

Amazing!

#artificial intelligence #boston dynamics #deep learning #reinforcement learning #robots

# New course! Reinforcement Learning in Python

January 27, 2017

I would like to announce my latest course – Artificial Intelligence: Reinforcement Learning in Python.

This has been one of my most requested topics since I started covering deep learning. This course has been brewing in the background for months.

The result: This is my most MASSIVE course yet.

Usually, my courses will introduce you to a handful of new algorithms (which is a lot for people to handle already). This course covers SEVENTEEN (17!) new algorithms.

This will keep you busy for a LONG time.

If you’re used to supervised and unsupervised machine learning, realize this: Reinforcement Learning is a whole new ball game.

There are so many new concepts to learn, and so much depth. It’s COMPLETELY different from anything you’ve seen before.

That’s why we build everything slowly, from the ground up.

There’s tons of new theory, but as you’ve come to expect, anytime we introduce new theory it is accompanied by full code examples.

What is Reinforcement Learning? It’s the technology behind self-driving cars, AlphaGo, video game-playing programs, and more.

You’ll learn that while deep learning has been very useful for tasks like driving and playing Go, it’s in fact just a small part of the picture.

Reinforcement Learning provides the framework that allows deep learning to be useful.

Without reinforcement learning, all we have is a basic (albeit very accurate) labeling machine.

With Reinforcement Learning, you have intelligence.

Reinforcement Learning has even been used to model processes in psychology and neuroscience. It’s truly the closest thing we have to “machine intelligence” and “general AI”.

COUPON:

https://www.udemy.com/artificial-intelligence-reinforcement-learning-in-python/?couponCode=EARLYBIRDSITE

#artificial intelligence #deep learning #reinforcement learning

# New Years Udemy Coupons! All Udemy Courses only $10 January 1, 2017 Act fast! These$10 Udemy Coupons expire in 10 days.

Ensemble Machine Learning: Random Forest and AdaBoost

Deep Learning Prerequisites: Linear Regression in Python

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Deep Learning Prerequisites: Logistic Regression in Python

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Deep Learning in Python

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Practical Deep Learning in Theano and TensorFlow

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Deep Learning: Convolutional Neural Networks in Python

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Unsupervised Deep Learning in Python

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Deep Learning: Recurrent Neural Networks in Python

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Advanced Natural Language Processing: Deep Learning in Python

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Easy Natural Language Processing in Python

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Cluster Analysis and Unsupervised Machine Learning in Python

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Unsupervised Machine Learning: Hidden Markov Models in Python

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Data Science: Supervised Machine Learning in Python

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Bayesian Machine Learning in Python: A/B Testing

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SQL for Newbs and Marketers

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How to get ANY course on Udemy for $10 (please use my coupons above for my courses): Click here for a link to all courses on the site: http://bit.ly/2iVkMTx Click here for a great calculus prerequisite course: http://bit.ly/2iwKpt2 Click here for a great Python prerequisite course: http://bit.ly/2iwQENC Click here for a great linear algebra 1 prerequisite course: http://bit.ly/2hHoLTn Click here for a great linear algebra 2 prerequisite course: http://bit.ly/2isjr3z Go to comments # New course! Ensemble Machine Learning in Python: Random Forest and AdaBoost December 25, 2016 [Skip to the bottom if you just want the coupon] This course is all about ensemble methods. We’ve already learned some classic machine learning models like k-nearest neighbor and decision tree. We’ve studied their limitations and drawbacks. But what if we could combine these models to eliminate those limitations and produce a much more powerful classifier or regressor? In this course you’ll study ways to combine models like decision trees and logistic regression to build models that can reach much higher accuracies than the base models they are made of. In particular, we will study the Random Forest and AdaBoost algorithms in detail. To motivate our discussion, we will learn about an important topic in statistical learning, the bias-variance trade-off. We will then study the bootstrap technique and bagging as methods for reducing both bias and variance simultaneously. We’ll do plenty of experiments and use these algorithms on real datasets so you can see first-hand how powerful they are. Since deep learning is so popular these days, we will study some interesting commonalities between random forests, AdaBoost, and deep learning neural networks. https://www.udemy.com/machine-learning-in-python-random-forest-adaboost/?couponCode=EARLYBIRDSITE2 Go to comments # New course! Bayesian Machine Learning in Python: A/B Testing November 17, 2016 [If you already know you want to sign up for my Bayesian machine learning course, just scroll to the bottom to get your$10 coupon!]

Boy, do I have some exciting news today!

You guys have already been keeping up with my deep learning series.

Hopefully, you’ve noticed that I’ve been releasing non-deep learning machine learning courses as well, in parallel (and they often tie into the deep learning series quite nicely).

Well today, I am announcing the start of a BRAND NEW series on Bayesian machine learning.

Bayesian methods require an entirely new way of thinking – a paradigm shift.

But don’t worry, it’s not just all theory.

In fact, the first course I’m releasing in the series is VERY practical – it’s on A/B testing.

Every online advertiser, e-commerce store, marketing team, etc etc etc. does A/B testing.

But did you know that traditional A/B testing is both horribly confusing and inefficient?

Did you know that there are cool, new adaptive methods inspired by reinforcement learning that improve on those old crusty tests?

(Those old methods, and the way they are traditionally taught, are probably the reason you cringe when you hear the word “statistics”)

Well, Bayesian methods not only represent a state-of-the-art solution to many A/B testing challenges, they are also surprisingly theoretically simpler!

You’ll end the course by doing your own simulation – comparing and contrasting the various adaptive A/B testing algorithms (including the final Bayesian method).

This is VERY practical stuff and any digital media, newsfeed, or advertising startup will be EXTREMELY IMPRESSED if you know this stuff.

This WILL advance your career, and any company would be lucky to have someone that knows this stuff on their team.

Awesome coincidence #1: As I mentioned above, a lot of these techniques cross-over with reinforcement learning, so if you are itching for a preview of my upcoming deep reinforcement learning course, this will be very interesting for you.

Awesome coincidence #2: Bayesian learning also crosses over with deep learning, one example being the variational autoencoder, which I may incorporate into a more advanced deep learning course in the future. They heavily rely on concepts from both Bayesian learning AND deep learning, and are very powerful state-of-the-art algorithms.

Due to all the black Friday madness going on, I am going to do a ONE-TIME ONLY $10 special for this course. With my coupons, the price will remain at$10, even if Udemy’s site-wide sale price goes up (which it will).

See you in class!

As promised, here is the coupon:

https://www.udemy.com/bayesian-machine-learning-in-python-ab-testing/?couponCode=EARLYBIRDSITE2

UPDATE: The Black Friday sale is over, but the early bird coupon is still up for grabs:

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LAST THING: Udemy is currently having an awesome Black Friday sale. $10 for ANY course starting Nov 15, but the price goes up by$1 every 2 days, so you need to ACT FAST.

I was going to tell you earlier but I was hard at work on my course. =)

Just click this link to get ANY course on Udemy for $10 (+$1 every 2 days): http://bit.ly/2fY3y5M

#bayesian #data science #machine learning #statistics