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 opportu
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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!**
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.
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!
Agenda:
5:00pm-5:30pm Checkin and networking
5:30PM Overview of the workshop and first 3 modules of MLCC
6:15PM: Break & Prayer
6:30PM: Pandas + Keras
7:30PM: Tensorflow MLCC modules
9:30PM: Event end
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