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#

fast-ai

Here are 24 public repositories matching this topic...

It is an Image Processing Challenge where we have to identify the Aerial Cactus using Deep Learning Techniques. I have used fastai library to make this work even easier.

  • UpdatedApr 20, 2019
  • Jupyter Notebook

This is simple image classifier of dogs and cats. This model classifies images based on their particular breeds.

  • UpdatedDec 14, 2019
  • Jupyter Notebook

becausehttps://cups.fast.ai/ could be a lot more UI/UX friendly :)@fastai

  • UpdatedAug 20, 2022
  • TypeScript

This project helps in analysis how employee is feeling the institution they are working on. Moreover, we are also summarizing the overall review given by employee according to section 'HR' of a company wants.

  • UpdatedMay 8, 2019
  • Jupyter Notebook

Bird Species Classifier built with Fast.ai 🐦

  • UpdatedMay 4, 2019
  • Jupyter Notebook

An Image Classification Model for Predicting Skin Diseases particularly in Rural India

  • UpdatedOct 21, 2021
  • Jupyter Notebook

Code and notes for the fast.ai deep learning course

  • UpdatedMay 22, 2017
  • Jupyter Notebook

An app which uses a pre-calculated model to classify tweet sentiment.

  • UpdatedSep 7, 2019
  • Jupyter Notebook

A small api which uses a pre-calculated model to classify bug images.

  • UpdatedSep 7, 2019
  • Jupyter Notebook

This project used Neural Networks and Deep Learning to classify pictures of checks whether they are blurry or not.

  • UpdatedOct 27, 2022
  • Jupyter Notebook

A deep learning model that detects whether a person has worn a mask or not, real-time.

  • UpdatedNov 28, 2020
  • Jupyter Notebook

Assignments from Deeplearning.ai and Fast.ai

  • UpdatedApr 8, 2018
  • Jupyter Notebook

Player detection for every cricketer playing in ICC Cricket World Cup 2019

  • UpdatedJun 1, 2021
  • Python

GitHub repo for fast.ai course project team #117

  • UpdatedOct 31, 2017

Based on yolov5 training mask wearing detection, and inference and deployment on faskai.

  • UpdatedJan 24, 2021
  • Python

This project used Neural Networks and Deep Learning to Classify Tweets into Positive, Negative, Neutral, Extremely Positive, and Extremely Negative

  • UpdatedOct 27, 2022
  • Jupyter Notebook

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