Machine Learning Study Jam

New to Machine Learning but don’t know where to start? Join us for a Machine Learning Study Jam where we will run through the Machine Learning Crash Course (MLCC)! This course is intended for those who wish to learn about ML from a practical, applied perspective that will enable you to use machine learning in your everyday projects and learn about the power of TensorFlow. This is a great opportun

May 18, 2019, 8:00 AM – 12:00 PM

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About this event

New to Machine Learning but don’t know where to start? Join us for a Machine Learning Study Jam where we will run through the Machine Learning Crash Course (MLCC)!

This course is intended for those who wish to learn about ML from a practical, applied perspective that will enable you to use machine learning in your everyday projects and learn about the power of TensorFlow. This is a great opportunity for anyone with basic technical knowledge and limited Machine Learning knowledge willing to gain some practical experience in ML and TensorFlow.

This course will be suitable for you, if:
*You are a strong programmer
*Ideally, you are at least somewhat familiar with Python. You don't need to be an expert.
*Ideally, you know at least a little about linear algebra and calculus.

This course is NOT recommended for:
*Participants with extensive machine learning backgrounds.
*Participants looking to learn about the lower-level intricacies of raw TensorFlow. Although the course does contain some basic TensorFlow exercises, most of the exercises focus on high-level Tensor APIs.
*Participants seeking advanced topics in machine learning such as image convolutional models and recurrent/sequential models.

**Bring your laptop and headphones! **

Agenda:
10h: event start & introductions
10:30h: overview & first 3 modules of MLCC
12:00h: 30 min break
12:30h: TensorFlow modules
14:00h: event end

Organizers

  • A. Rosa Castillo

    Fortris

    GDG Organizer

  • Carlos Caballero

    GDG Organizer

  • Cristina D.

    GDG Organizer

  • Alba Ruiz Gutiérrez

    Software Engineering Student

  • José Antonio Palacios Ramírez

    Organizer

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