IAP 2018 Activities by Sponsor - Office of Educational Innovation and Technology

JM.Modisette, PhD, Technical Evangelist

Jan/24

Wed

10:00AM-12:00PM

3-270

Enrollment: Register on MathWorks Website (below)
Limited to 119 participants
Prereq: None

Are you new to deep learning and want to learn how to use it in your work?  Deep learning can achieve state-of-the-art accuracy in many humanlike tasks such as naming objects in a scene or recognizing optimal paths in an environment.

The main tasks are to assemble large data sets, create a neural network, to train, visualize, and evaluate different models, using specialized hardware - often requiring unique programming knowledge. These tasks are frequently even more challenging because of the complex theory behind them.

In this seminar, we’ll demonstrate new MATLAB features that simplify these tasks and eliminate the low-level programming. In doing so, we’ll decipher practical knowledge of the domain of deep learning.  We’ll build and train neural networks that recognize handwriting, classify food in a scene, and figure out the drivable area in a city environment.  

For more information and registration at:

https://www.mathworks.com/company/events/seminars/mit-iap-2361872.html

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com

JM.Modisette, Phd, Technical Evangelist

Jan/22

Mon

10:00AM-02:00PM

32-141, Attendees should bring a laptop

Enrollment: Register on MathWorks Website (below)
Limited to 90 participants
Prereq: None

In this hands-on workshop, you will learn how to import data from an external file, plot the data over time, then perform some analysis to view the data trends.  You’ll learn how to write a MATLAB script and publish it to a format for sharing, such as HTML. You’ll also learn how to write your own MATLAB functions, use flow control, and create loops.

By the end of the session, you’ll have learned to create an application in MATLAB.

 

Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2341781.html 

Note: Attendees should bring a laptop to this hands-on lab.

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com

JM.Modisette, Phd, Technical Evangelist

Jan/22

Mon

02:30PM-06:30PM

W31-301

Enrollment: Register on MathWorks Website (below)
Limited to 30 participants
Prereq: No Simulink experience is assumed or necessary.

This workshop is a 4-hour hands-on tutorial of Simulink, the block diagram environment integrated with MATLAB for multidomain simulation and design.

During the workshop, you will follow along with the presenter in creating a Simulink model from scratch and then building upon and improving that model throughout the session. You’ll get an introduction to many Simulink features, including:

- Modeling a dynamic system

- Logic operations

- Model hierarchy

- Masks

- Creating custom libraries

- Model referencing

- Vectorization

 

Learn how Simulink is used for the following applications:

- Modeling continuous systems

- Control system development

- Algorithm design and simulation

 

 Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2341781.html%20.html

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com

JM.Modisette, Phd, Technical Evangelist

Jan/23

Tue

10:00AM-12:00PM

3-270

Enrollment: Limited: First come, first served (no advance sign-up)
Limited to 119 participants
Prereq: None

Large-scale simulations and data processing tasks that support engineering and scientific activities such as mathematical modeling, algorithm development, and testing can take an unreasonably long time to complete or require a lot of computer memory. You can speed up these tasks by taking advantage of high-performance computing resources, such as multicore computers, GPUs, computer clusters, and cloud computing services.

Using the Parallel Computing capabilities in MATLAB allows you to take advantage of additional hardware resources that may be available either locally on your desktop or on clusters and clouds. By using more hardware, you can reduce the cycle time for your workflow and solve computationally and data-intensive problems faster.   

We will discuss and demonstrate how to perform parallel and distributed computing in MATLAB. We will introduce you to parallel processing constructs such as parallel for-loops, distributed arrays, and message-passing functions. We will also show you how to take advantage of common trends in computer hardware, from multiprocessor machines to computer clusters.

Highlights Include:

-Built-in support for parallel computing

-Creating parallel applications

-Scaling up to computer clusters, grid environments or clouds

-Employing GPUs

-Programming with tall and distributed arrays to work with large data sets

 

Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2362013.html

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com

JM.Modisette, PhD, Technical Evangelist

Jan/23

Tue

01:00PM-04:00PM

W31-301

Enrollment: Register on MathWorks Website (below)
Limited to 30 participants

Following the Parallel and Distributed Computing Seminar, this workshop will allow attendees to practice different techniques for parallel and distributed computing.

Highlights include:

- 5-minute introduction to resources at MIT

- 20-minute overview of Parallel Computing with MATLAB

- 1.5 hour hands-on, self-paced workshop

- 30-minute Q&A session of workshop

- 30-minute hands-on session of submitting job to cluster

 

Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2362013.html

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com

JM.Modisette, PhD, Technical Evangelist, MathWorks

Jan/24

Wed

01:00PM-04:00PM

W31-301

Enrollment: Register on MathWorks Website (below)
Limited to 30 participants

Are you new to deep learning and want to learn how to apply these techniques it in your work? Deep learning achieves human-like accuracy for many tasks considered algorithmically unsolvable with traditional machine learning. It is frequently used to develop applications such as face recognition, automated driving, and image classification.

In this hands-on workshop, you will write code and use MATLAB to:

- Learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss”

- Build a deep network that can classify your own handwritten digits

- Access and explore various pretrained models

- Use transfer learning to build a network that classifies different types of food

- Train deep learning networks on GPUs in the cloud

- Learn how to use GPU code generation technology to accelerate inference performance

 

Register at: https://www.mathworks.com/company/events/seminars/mit-iap-2361872.html

Sponsor(s): Office of Educational Innovation and Technology
Contact: JM.Modisette, JM.Modisette@mathworks.com