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Artificial Intelligence, deep learning, machine learning - whatever you're doing if you don't understand it - learn it. Because otherwise you're going to be a dinosaur within 3 years. - Mark Cuban
 
Machine learning is creating a global business revolution & it's not going to stop. Leading companies like Google, Amazon, & Facebook are betting their futures on AI. Even engineers who have had success in the past need to continue their technical education as startups & organizations of all kinds can't hire AI & machine learning engineers fast enough. While there are plenty of online resources, we know it's tough to learn a technical topic without a teacher. We're bringing together expert engineers in the field of machine learning, deep learning & AI who will help you learn the basics in a hands-on & action-packed day. 
The course is expertly designed to leave you with the ability to take training data, do feature selection & actually build models for applications like content categorization, sentiment analysis, & image recognition. By the end of the day, students will be able to use models in their day-to-day work. You will also walk away with a high-level understanding of how common models such as Deep Neural Networks, SVMs, Logistic Regression & Naive Bayes work & when to use them.
Technologies Introduced
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Intro to Machine Learning
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Scikit-learn
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Numpy
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Jupyter
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Intro to Machine Learning Platforms
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Azure ML
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Amazon ML
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IBM Watson
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Intro to Deep Learning
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TensorFlow
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Keras
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</UL>
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Prerequisites
We try to make this class as accessible as possible. Some proficiency with Python is necessary. If you can open up a Jupyter notebook & install requisite software that's helpful but we'll also cover how to do that quickly in the beginning.
What will be provided
We will provide all the food, drinks & coffee your heart desires as well as provide the leave behind tools & resources for your continued success.
What you Need to bring
You must also bring your own laptop (don't forget your charger). If you bring a laptop with a GPU that supports CUDA (for example a MacBook with Mac OS X 10.11 or later), we'll see if we can make it GPU accelerated.
Talent
Lukas Biewald: Lukas Biewald is the founder of CrowdFlower, an Artificial Intelligence company that works with data science teams at Google, Bloomberg, Facebook & hundreds of other organizations to make machine learning work in the real world. Prior to that, Lukas was the first data scientist at Powerset (Acquired by Microsoft & rebranded as Bing) & a scientist at Yahoo!, Lukas was shipping machine learning algorithms to hundreds of millions of users. 
Lukas frequently teaches invited Machine Learning workshops with Galvanize, O'Reilly & ODSC. He was a TA for Stanford's machine learning class in 2003. He is a frequent contributor to Computerworld, Forbes & O'Reilly & has presented at the best-known machine learning-related academic conferences such as AAAI, SIGIR, ACL & EMNLP. He's had the honor of being in Inc's annual 30 under 30 & was also a finalist at TechCrunch Disrupt.
Curriculum
9:00 - 10:00 Breakfast & Install Requisite Software
We always take it as a personal challenge to get the prerequisite machine learning software installed on everyone's laptop. We can all learn to uplevel our unix-fu by helping each other get set up.
10:00 - 12:00 Build a Sentiment Classifier From Scratch
Everyone builds a Twitter sentiment classifier using scikit-learn. We try multiple feature selection approaches & multiple model types. We learn some common tricks for actually making machine learning effective in the real world.
12:00-1:00 Lunch & History/Theory of Machine Learning
Eat lunch & for your dining entertainment, Lukas will introduce a little math, stats & history of how machine learning got to where it is today.
1:00-2:30 Try the Common Machine Learning Platforms
These days, there are many excellent, low cost machine learning platforms. We will try rebuilding our sentiment classifier on two of the most common: Microsoft Azure ML, Amazon ML IBM Watson. If students want to try Google Predict or Salesforce Einstein we can do that too.
2:30-3:00 Break & Q&A
We can discuss other applications of this technology & look at how it might apply to real-world tasks that students may be working on.
3:00-5:00 Introduction to TensorFlow & Deep Neural Networks
We will learn how deep neural networks work & actually build one! If you bring a laptop with a GPU that supports CUDA (for example a MacBook with Mac OS X 10.11 or later), we'll see if we can make it GPU accelerated.
We'll all build a network to do handwritten digit recognition.
5:00-5:30 Wrap up & Q&A
We will finish up & discuss how to apply this knowledge directly to problems that we actually face in our jobs.
5:30-7:00 Drinks & Networking
We'll bring together top entrepreneurs, tech executives & engineers to connect with & learn from. Plus, this is a chance to meet your classmates & teachers in an informal & fun setting.
Corporate Training:
We will host a custom & private 1 or 2 day seminar on your campus. This is ideal for organizations looking to build deep learning expertise in-house & want to customize our courses to fit your business needs.