Machine Learning

Machine Learning

Video Training

With the growing prominence of data science and its uses across all types of business, it’s the perfect time to start applying machine learning. In this Learning Path, you’ll master everything you need to transform data into action. Start with basic techniques and move on to coding your own machine learning algorithms.

Below are the video training courses included in this Learning Path.

1

Hilary Mason: An Introduction to Machine Learning with Web Data

Presented by Hilary Mason 2 hours 43 minutes

Wondering what to do with all the data you’ve accumulated through your web application? Begin your study of machine learning as bit.ly lead scientist Hilary Mason shows you how to solve data analysis problems using basic machine learning techniques and frameworks. Follow examples as you acquire skills for obtaining, cleaning, and exploring data to building a model and interpreting the results.

2

Hilary Mason: Advanced Machine Learning

Presented by Hilary Mason 2 hours 13 minutes

In this step, bit.ly lead scientist Hilary Mason shows you how to solve real-world problems with machine learning. Using real data from an actual ecommerce website, you will apply production quality algorithms to understand all the issues that arise when working in a live environment. Learn how to apply best practices to common types of machine learning problems, extract quantifiable data, and explore several open source tools and how to use them.

3

Deep Learning

Presented by O’Reilly Media, Inc. 2 hours 2 minutes

In this step you’ll move toward artificial intelligence with neural networks and machine learning. Through a series of presentations by machine learning experts from Google, Stanford University, and UC Berkeley, you’ll learn about deep neural networks, scalable computational tools for large-scale data analysis, and speech and visual object recognition.

4

Learning Data Structures and Algorithms

Presented by Rod Stephens 7 hours 32 minutes

Now you are ready to analyze and implement common algorithms used in data processing. You’ll start by learning about the complexity theory, then jump into learning about numerical algorithms. From there, you will go on to linked lists, searching, hash tables, recursion, and backtracking algorithms. Finally, you will cover trees, balanced trees, decision trees, and network algorithms.

5

Hardcore Data Science NYC 2014

Presented by O’Reilly Media, Inc. 5 hours 7 minutes

This step includes a collection of presentations from Strata + Hadoop World in New York to teach you about data management, natural language processing, crowdsourcing, and algorithm design. You’ll learn techniques for computing quantities, gathering data efficiently, interpreting workflows, and understanding metrics from social media. You’ll also see how data appears to machines, as opposed to humans, how machines understand music, and how to turn data into insights.

6

Hardcore Data Science California 2015

Presented by O’Reilly Media, Inc. 5 hours 43 minutes

This step of your Learning Path introduces you to emerging technologies and cutting-edge practices in the field of machine learning through a series of presentations from from Strata + Hadoop World in California. You’ll expand your understanding of speech recognition and acoustic modeling; learn theoretical tradeoffs between statistical risk, amount of data, and “externalities” such as computation, communication, and privacy; look at developments in computer vision, and many other topics.