What we're about

Fast.ai (www.fast.ai/) “making neural network uncool again” is a MOOC (Massive Open Online Courses). It is designed to make deep learning easier to use while using cutting-edge research. The goal is to get more people from all backgrounds involved in the field of deep learning to widen its application impact.

It follows a "Top-down” approach, which is exactly like how we learn a sport. We start by trying to play it, without worrying about rules. Once we are confident, we learn the rules and tricks one by one. This approach favors exploration first and investigation second, so from the very first lesson, you are able to build up your own image recognition with very few lines of codes.

This study group is FREE, its aims are:
* to nurture the study of deep learning from the Fast.ai courses (www.course.fast.ai/)
* to connect beginners and experts interested in the Fast.ai library and courses
* to showcase projects from participants who have completed the lessons on computer vision, Natural Language Processing (NLP), Tabular Data, and Collaborative filtering.

To work on Fast.ai lessons, you will need a cloud GPU provider which has the Fast.ai library installed, two free solutions recommended: Kaggle or Colab from Google.
Additional cloud solutions are possible via this link. You will need to be also familiar with the Jupyter Notebook environment.

Participants should have at least one year of coding experience with Python and have knowledge about the numpy and pandas modules.

Upcoming events (3)

Lesson 4 - NLP - Tabular Data - Collaborative Filtering - Pudong Location

In lesson 4, we will dive into Natural Language Processing (NLP) with the IMDB database that holds movies reviews, so a nice way to explore sentiment analysis regarding a particular movie. Additional topics covered are: Language modeling Deeper dive into NLP transfer learning Text classification Tabular data Collaborative filtering Embeddings Neural network: what's happening mathematically And as usual, we will start by showcasing fastai students projects and answering questions from the past lessons.

Lesson 4 - NLP - Tabular Data - Collaborative Filtering - Yangpu Location

In lesson 4, we will dive into Natural Language Processing (NLP) with the IMDB database that holds movies reviews, so a nice way to explore sentiment analysis regarding a particular movie. Additional topics covered are: Language modeling Deeper dive into NLP transfer learning Text classification Tabular data Collaborative filtering Embeddings Neural network: what's happening mathematically And as usual, we will start by showcasing fastai students projects and answering questions from the past lessons.

Lesson 4 - NLP - Tabular Data - Collaborative Filtering - Xuhui Location

In lesson 4, we will dive into Natural Language Processing (NLP) with the IMDB database that holds movies reviews, so a nice way to explore sentiment analysis regarding a particular movie. Additional topics covered are: Language modeling Deeper dive into NLP transfer learning Text classification Tabular data Collaborative filtering Embeddings Neural network: what's happening mathematically And as usual, we will start by showcasing fastai students projects and answering questions from the past lessons.

Photos (15)