• What we'll do
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.

**Bring your laptop!**

Agenda:

17:30 Intro: Prerequisites check, Overview of MLCC, Briefly explain target audience, topics and scope of course, modality of content (videos, docs, Playground, Colab exercises), follow up sessions and hangouts for next 4 weeks.

18:00 Discuss material together of next three modules of MLCC:
Framing - 20 min (Nana)

Descending into ML - 20 min (Nana)

18:40 Break for pizza

19:00 Reducing Loss - 60 min (Atif)

20:00 Split into pairs to do the CYU and Playground exercises

20:15 Watch First Steps with TF video and do the 5 exercises in the module (Atif)

21:15 Wrap Up and explain follow up sessions (Perusha)

We’re super excited to bring Google's latest Machine Learning offering - ‘Machine Learning Crash Course (MLCC)’ to GDG Reading and Thames Valley. This course is intended for those who wish to learn about ML from a practical, applied perspective that will enable them to use machine learning within their everyday projects, and who wish to benefit from the power of TensorFlow wrapped in convenient higher-level abstractions. This is a great opportunity for professionals, entrepreneurs and students to gain some practical experience in ML and TensorFlow.

What? The Machine Learning Crash Course with TensorFlow APIs.

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.

You can take a look at the pre-requisites and pre-work here:
https://developers.google.com/machine-learning/crash-course/prereqs-and-prework

Format of this course
We will be walking you through MLCC, it’s modules and basic ML concepts.

Additionally, we will have you go through selected modules of the course, with a teaching assistant guiding you in course’s practical pieces/exercises and troubleshooting and pieces of the content where you are struggling.

The course is open to all so you can complete the remaining modules as a self-study after the session. Other requirements?

Additionally, we’d need you to bring:
* Your laptop and charger. You will need this to go through the online course.
* Pen & paper (or any other preferable option if you plan to take notes)
* A can-do attitude!