Intro to Machine Learning - Part 1

Intro to Machine Learning Part 1.

Instructor: Dr. Michael Bowles

This is an intense, one-day short-course aimed at programmers wanting to learn machine learning. The course takes a very hands-on, run-code approach. 

9:30 am Registration
10:00 am - 5:00 pm Class (w. break for lunch - delivered)

Class will be delivered by webcast for those want to attend remotely.  To get the webcast instructions you must sign up on eventbrite 12 hours prior to start of class.

Class Outline:
1. Review of R programming
2. Description of basic machine learning problems
3. Types of data - structured, unstructured, similarity measures, preprocessing
4. Data exploration - statistical summaries, visualization
5. Model complexity, over-fitting and measuring overfitting
6. Sample algorithms and model selection approaches.

Who Should Attend:
The class is aimed at computer programmers, computer scientists and software engineers who want to gain a working knowledge of modern machine learning and the types of problems that it can solve. Class sessions will rely heavily on code examples in R statistical programming language.  Participants aren't expected to have any prior experience with R. An introduction to R will be included in the material. The material will cover an introduction to R statistical programming language, unsupervised learning (clustering) and supervised learning (predicting classification and regression – also called "predictive analytics").

-pre-pay by credit card
($225 for registration 5 days ahead of event, $275 otherwise)

-or bring cash or check.


For more details see:


Join or login to comment.

  • Christian

    Great intro to machine learning and R

    February 25, 2013

    • Mike B.

      Christian, I'm happy that you liked the class. Thanks for the kind words. It was fun having you in class. Look forward to seeing you in another.

      February 25, 2013

  • holden c.

    sorry, had an urgent personal matter

    February 23, 2013



    Are you going to teach Machine Learning on Big Data in the near future? I missed that series.

    February 13, 2013

    • Mike B.

      Ronald, a number of people have said the same thing. I'm thinking of running the class again - probably in the May time-frame. You can watch this meetup or you can send me an email and I'll email you when I announce future classes.

      February 13, 2013

    • RONALD K.

      Thanks Mike. Now for this upcoming class, are you emphasizing on R programming or the machine learning algorithms itself? I am pretty comfortable with R, but I want to learn more about machine learning algorithms.

      1 · February 14, 2013

  • Mike B.

    There are three parts to the sequence. They can be taken in any order. The first outlines the basic problems that machine learning can solve and common problems and solutions. The second covers unsupervised learning. The third covers unsupervised learning (clustering primarily). There will be a separate charge for each part. The other two are already scheduled over the course of the next month or so.

    February 11, 2013

  • Uma K.

    How many Parts does this sequence have?

    Does the fee include all parts or only part 1?


    February 7, 2013

12 went

Your organizer's refund policy for Intro to Machine Learning - Part 1

Refunds offered if:

  • the Meetup is cancelled
  • you can cancel at least 5 day(s) before the Meetup

Payments you make go to the organizer, not to Meetup. You must make refund requests to the organizer.

Our Sponsors

  • Amazon AWS

    Free compute time for working group events

  • Cloudera

    Access to Hadoop contributors

  • Safari Online Books

    Free subscription for Apache Bigtop Working Group members.


    Technical support, meeting space, and access to GPUs

People in this
Meetup are also in:

Create your own Meetup Group

Get started Learn more

I'm surpris ed by the level of growth I've seen since becoming an organizer, it's given me more confidence in my abilities.

Katie, started NYC ICO

Sign up

Meetup members, Log in

By clicking "Sign up" or "Sign up using Facebook", you confirm that you accept our Terms of Service & Privacy Policy